Potato Plantlet Inoculation Graphs

library(tidyverse)
library(gridExtra)

Attaching package: ‘gridExtra’

The following object is masked from ‘package:dplyr’:

    combine

library(cowplot)

********************************************************
Note: As of version 1.0.0, cowplot does not change the
  default ggplot2 theme anymore. To recover the previous
  behavior, execute:
  theme_set(theme_cowplot())
********************************************************

Add Batch ID to Wet Weight Dataframes

# add batch id variable to each dataset
## Set 1
### Wet Shoot
set_1_WS_id <- set_1_WS
set_1_WS_id$batch <- c("Set 1")
### Wet Root
set_1_WR_id <- set_1_WR
set_1_WR_id$batch <- c("Set 1")
## Set 2.1
### Wet Shoot
set_2.1_WS_id <- set_2.1_WS
set_2.1_WS_id$batch <- c("Set 2.1")
### Wet Root
set_2.1_WR_id <- set_2.1_WR
set_2.1_WR_id$batch <- c("Set 2.1")
## Set 2.2
### Wet Shoot
set_2.2_WS_id <- set_2.2_WS
set_2.2_WS_id$batch <- c("Set 2.2")
### Wet Root
set_2.2_WR_id <- set_2.2_WR
set_2.2_WR_id$batch <- c("Set 2.2")
## Set 2.3
### Wet Shoot
set_2.3_WS_id <- set_2.3_WS
set_2.3_WS_id$batch <- c("Set 2.3")
### Wet Root
set_2.3_WR_id <- set_2.3_WR
set_2.3_WR_id$batch <- c("Set 2.3")
## Set 2.4
### Wet Shoot
set_2.4_WS_id <- set_2.4_WS
set_2.4_WS_id$batch <- c("Set 2.4")
### Wet Root
set_2.4_WR_id <- set_2.4_WR
set_2.4_WR_id$batch <- c("Set 2.4")
## Set 3.1
### Wet Shoot
set_3.1_WS_id <- set_3.1_WS
set_3.1_WS_id$batch <- c("Set 3.1")
### Wet Root
set_3.1_WR_id <- set_3.1_WR
set_3.1_WR_id$batch <- c("Set 3.1")
## Set 3.2
### Wet Shoot
set_3.2_WS_id <- set_3.2_WS
set_3.2_WS_id$batch <- c("Set 3.2")
### Wet Root
set_3.2_WR_id <- set_3.2_WR
set_3.2_WR_id$batch <- c("Set 3.2")
## Set 3.3
### Wet Shoot
set_3.3_WS_id <- set_3.3_WS
set_3.3_WS_id$batch <- c("Set 3.3")
### Wet Root
set_3.3_WR_id <- set_3.3_WR
set_3.3_WR_id$batch <- c("Set 3.3")
## Set 3.4
### Wet Shoot
set_3.4_WS_id <- set_3.4_WS
set_3.4_WS_id$batch <- c("Set 3.4")
### Wet Root
set_3.4_WR_id <- set_3.4_WR
set_3.4_WR_id$batch <- c("Set 3.4")
## Set 3.5
### Wet Shoot
set_3.5_WS_id <- set_3.5_WS
set_3.5_WS_id$batch <- c("Set 3.5")
### Wet Root
set_3.5_WR_id <- set_3.5_WR
set_3.5_WR_id$batch <- c("Set 3.5")
## Set 4.1
### Wet Shoot
set_4.1_WS_id <- set_4.1_WS
set_4.1_WS_id$batch <- c("Set 4.1")
### Wet Root
set_4.1_WR_id <- set_4.1_WR
set_4.1_WR_id$batch <- c("Set 4.1")
## Set 4.2
### Wet Shoot
set_4.2_WS_id <- set_4.2_WS
set_4.2_WS_id$batch <- c("Set 4.2")
### Wet Root
set_4.2_WR_id <- set_4.2_WR
set_4.2_WR_id$batch <- c("Set 4.2")
## Set 4.3
### Wet Shoot
set_4.3_WS_id <- set_4.3_WS
set_4.3_WS_id$batch <- c("Set 4.3")
### Wet Root
set_4.3_WR_id <- set_4.3_WR
set_4.3_WR_id$batch <- c("Set 4.3")

Group the Data for Plotting

#Group the datasets based on Sample ID and prep method
## Set 1
set_1_WS_grouped <- group_by(set_1_WS_id, isolate, sample, batch)
set_1_WR_grouped <- group_by(set_1_WR_id, isolate, sample, batch)
## Set 2.1
set_2.1_WS_grouped <- group_by(set_2.1_WS_id, isolate, sample, batch)
set_2.1_WR_grouped <- group_by(set_2.1_WR_id, isolate, sample, batch)
## Set 2.2
set_2.2_WS_grouped <- group_by(set_2.2_WS_id, isolate, sample, batch)
set_2.2_WR_grouped <- group_by(set_2.2_WR_id, isolate, sample, batch)
## Set 2.3
set_2.3_WS_grouped <- group_by(set_2.3_WS_id, isolate, sample, batch)
set_2.3_WR_grouped <- group_by(set_2.3_WR_id, isolate, sample, batch)
## Set 2.4
set_2.4_WS_grouped <- group_by(set_2.4_WS_id, isolate, sample, batch)
set_2.4_WR_grouped <- group_by(set_2.4_WR_id, isolate, sample, batch)
## Set 3.1
set_3.1_WS_grouped <- group_by(set_3.1_WS_id, isolate, sample, batch)
set_3.1_WR_grouped <- group_by(set_3.1_WR_id, isolate, sample, batch)
## Set 3.2
set_3.2_WS_grouped <- group_by(set_3.2_WS_id, isolate, sample, batch)
set_3.2_WR_grouped <- group_by(set_3.2_WR_id, isolate, sample, batch)
## Set 3.3
set_3.3_WS_grouped <- group_by(set_3.3_WS_id, isolate, sample, batch)
set_3.3_WR_grouped <- group_by(set_3.3_WR_id, isolate, sample, batch)
## Set 3.4
set_3.4_WS_grouped <- group_by(set_3.4_WS_id, isolate, sample, batch)
set_3.4_WR_grouped <- group_by(set_3.4_WR_id, isolate, sample, batch)
## Set 3.5
set_3.5_WS_grouped <- group_by(set_3.5_WS_id, isolate, sample, batch)
set_3.5_WR_grouped <- group_by(set_3.5_WR_id, isolate, sample, batch)
## Set 4.1
set_4.1_WS_grouped <- group_by(set_4.1_WS_id, isolate, sample, batch)
set_4.1_WR_grouped <- group_by(set_4.1_WR_id, isolate, sample, batch)
## Set 4.2
set_4.2_WS_grouped <- group_by(set_4.2_WS_id, isolate, sample, batch)
set_4.2_WR_grouped <- group_by(set_4.2_WR_id, isolate, sample, batch)
## Set 4.3
set_4.3_WS_grouped <- group_by(set_4.3_WS_id, isolate, sample, batch)
set_4.3_WR_grouped <- group_by(set_4.3_WR_id, isolate, sample, batch)

Create Stats Functions

# Creating a function that provides 95% CI for the data vector using a t-distribution
conf_int95 <- function(data) {
    n <- length(data)
    error <- qt(0.975, df=n-1) * sd(data, na.rm = TRUE)/sqrt(n)
    return(error)
}
# Create a function that calculates the standard error for the data
std_error <- function(data) {
  n <- length(data)
  se <- sd(data, na.rm = TRUE)/sqrt(n)
  return(se)
}

Compute stats over triplicates for plotting

# set 1
stat_set_1_WS <- summarise(set_1_WS_grouped, N=length(mg), Average=mean(mg, na.rm = TRUE), CI95=conf_int95(mg), SE=std_error(mg))
stat_set_1_WR <- summarise(set_1_WR_grouped, N=length(mg), Average=mean(mg, na.rm = TRUE), CI95=conf_int95(mg), SE=std_error(mg))
# set 2.1
stat_set_2.1_WS <- summarise(set_2.1_WS_grouped, N=length(mg), Average=mean(mg, na.rm = TRUE), CI95=conf_int95(mg), SE=std_error(mg))
stat_set_2.1_WR <- summarise(set_2.1_WR_grouped, N=length(mg), Average=mean(mg, na.rm = TRUE), CI95=conf_int95(mg), SE=std_error(mg))
# set 2.2
stat_set_2.2_WS <- summarise(set_2.2_WS_grouped, N=length(mg), Average=mean(mg, na.rm = TRUE), CI95=conf_int95(mg), SE=std_error(mg))
stat_set_2.2_WR <- summarise(set_2.2_WR_grouped, N=length(mg), Average=mean(mg, na.rm = TRUE), CI95=conf_int95(mg), SE=std_error(mg))
# set 2.3
stat_set_2.3_WS <- summarise(set_2.3_WS_grouped, N=length(mg), Average=mean(mg, na.rm = TRUE), CI95=conf_int95(mg), SE=std_error(mg))
stat_set_2.3_WR <- summarise(set_2.3_WR_grouped, N=length(mg), Average=mean(mg, na.rm = TRUE), CI95=conf_int95(mg), SE=std_error(mg))
# set 2.4
stat_set_2.4_WS <- summarise(set_2.4_WS_grouped, N=length(mg), Average=mean(mg, na.rm = TRUE), CI95=conf_int95(mg), SE=std_error(mg))
stat_set_2.4_WR <- summarise(set_2.4_WR_grouped, N=length(mg), Average=mean(mg, na.rm = TRUE), CI95=conf_int95(mg), SE=std_error(mg))
# set 3.1
stat_set_3.1_WS <- summarise(set_3.1_WS_grouped, N=length(mg), Average=mean(mg, na.rm = TRUE), CI95=conf_int95(mg), SE=std_error(mg))
stat_set_3.1_WR <- summarise(set_3.1_WR_grouped, N=length(mg), Average=mean(mg, na.rm = TRUE), CI95=conf_int95(mg), SE=std_error(mg))
# set 3.2
stat_set_3.2_WS <- summarise(set_3.2_WS_grouped, N=length(mg), Average=mean(mg, na.rm = TRUE), CI95=conf_int95(mg), SE=std_error(mg))
stat_set_3.2_WR <- summarise(set_3.2_WR_grouped, N=length(mg), Average=mean(mg, na.rm = TRUE), CI95=conf_int95(mg), SE=std_error(mg))
# set 3.3
stat_set_3.3_WS <- summarise(set_3.3_WS_grouped, N=length(mg), Average=mean(mg, na.rm = TRUE), CI95=conf_int95(mg), SE=std_error(mg))
stat_set_3.3_WR <- summarise(set_3.3_WR_grouped, N=length(mg), Average=mean(mg, na.rm = TRUE), CI95=conf_int95(mg), SE=std_error(mg))
# set 3.4
stat_set_3.4_WS <- summarise(set_3.4_WS_grouped, N=length(mg), Average=mean(mg, na.rm = TRUE), CI95=conf_int95(mg), SE=std_error(mg))
stat_set_3.4_WR <- summarise(set_3.4_WR_grouped, N=length(mg), Average=mean(mg, na.rm = TRUE), CI95=conf_int95(mg), SE=std_error(mg))
# set 3.5
stat_set_3.5_WS <- summarise(set_3.5_WS_grouped, N=length(mg), Average=mean(mg, na.rm = TRUE), CI95=conf_int95(mg), SE=std_error(mg))
stat_set_3.5_WR <- summarise(set_3.5_WR_grouped, N=length(mg), Average=mean(mg, na.rm = TRUE), CI95=conf_int95(mg), SE=std_error(mg))
# set 4.1
stat_set_4.1_WS <- summarise(set_4.1_WS_grouped, N=length(mg), Average=mean(mg, na.rm = TRUE), CI95=conf_int95(mg), SE=std_error(mg))
stat_set_4.1_WR <- summarise(set_4.1_WR_grouped, N=length(mg), Average=mean(mg, na.rm = TRUE), CI95=conf_int95(mg), SE=std_error(mg))
# set 4.2
stat_set_4.2_WS <- summarise(set_4.2_WS_grouped, N=length(mg), Average=mean(mg, na.rm = TRUE), CI95=conf_int95(mg), SE=std_error(mg))
stat_set_4.2_WR <- summarise(set_4.2_WR_grouped, N=length(mg), Average=mean(mg, na.rm = TRUE), CI95=conf_int95(mg), SE=std_error(mg))
# set 4.3
stat_set_4.3_WS <- summarise(set_4.3_WS_grouped, N=length(mg), Average=mean(mg, na.rm = TRUE), CI95=conf_int95(mg), SE=std_error(mg))
stat_set_4.3_WR <- summarise(set_4.3_WR_grouped, N=length(mg), Average=mean(mg, na.rm = TRUE), CI95=conf_int95(mg), SE=std_error(mg))

Wet Weight Plots

Set 1

Wet Shoot

With NAs

# ggplot with bars
## set the control value for Wet Shoot mg
## remove control-WO
stat_set_1_WS_NAs <- filter(stat_set_1_WS, isolate != "control-WO")
set_1_WS_control_int <- as.numeric(stat_set_1_WS[58,5])
#set_1_WS_control_int
set_1_WS_bars_NA <- ggplot(stat_set_1_WS_NAs, aes(x = isolate, y = Average))
set_1_WS_bars_NA <- set_1_WS_bars_NA + geom_bar(stat = "identity", size=.5, fill="lightgreen")
set_1_WS_bars_NA <- set_1_WS_bars_NA + geom_hline(yintercept=set_1_WS_control_int, colour="#990000", linetype="dashed")
set_1_WS_bars_NA <- set_1_WS_bars_NA + labs(x="", y="Shoot - Fresh Weight (mg)")
set_1_WS_bars_NA <- set_1_WS_bars_NA + geom_errorbar(aes(ymin=Average-SE, ymax=Average+SE), size=.5, width=.2)
set_1_WS_bars_NA <- set_1_WS_bars_NA + theme(axis.text.x = element_text(angle = 75, hjust = 1, size = 12),
                                       axis.text.y = element_text(size = 12),
                                       axis.title.x = element_blank(),
                                       axis.title.y = element_text(size = 14),
                                       legend.text = element_text(size = 16),
                                       legend.title = element_text(size = 16))
set_1_WS_bars_NA <- set_1_WS_bars_NA + scale_x_discrete(position = "bottom", expand = c(0,0))
set_1_WS_bars_NA <- set_1_WS_bars_NA + scale_y_continuous(expand = c(0,0))
set_1_WS_bars_NA <- set_1_WS_bars_NA + geom_text(aes(x=1, y=650, label="Stretch it"), vjust=-1)
set_1_WS_bars_NA

Removed NAs

# ggplot with bars
## remove isoaltes with NA values
stat_s1_WS_complete <- stat_set_1_WS[complete.cases(stat_set_1_WS),]
## remove control-WO
stat_s1_WS_complete <- filter(stat_s1_WS_complete, isolate != "control-WO")
## set the control value for Wet Shoot mg
set_1_WS_control_int <- as.numeric(stat_s1_WS_complete[39,5])
## calculate % control for each treatment
stat_s1_WS_complete$control <- as.numeric(stat_s1_WS_complete[39,5])
stat_s1_WS_complete <- mutate(stat_s1_WS_complete, p_ctrl = (100* (Average / control)))
## Make the plot
set_1_WS_bars <- ggplot(stat_s1_WS_complete, aes(x = isolate, y = Average))
set_1_WS_bars <- set_1_WS_bars + geom_bar(stat = "identity", size=.5, fill="lightgreen")
set_1_WS_bars <- set_1_WS_bars + geom_hline(aes(yintercept=set_1_WS_control_int), colour="#990000", linetype="dashed")
set_1_WS_bars <- set_1_WS_bars + labs(x="", y="Shoot - Fresh Weight (mg)")
set_1_WS_bars <- set_1_WS_bars + geom_errorbar(aes(ymin=Average-SE, ymax=Average+SE), size=.5, width=.2)
#set_1_WS_bars <- set_1_WS_bars + geom_text(aes(label=sprintf("%0.0f", round(p_ctrl, digits = 0)), y=Average+SE, vjust=-0.5), hjust = 0, angle = 45)
set_1_WS_bars <- set_1_WS_bars + theme(axis.text.x = element_text(angle = 60, hjust = 1, size = 12),
                                       axis.text.y = element_text(size = 12),
                                       axis.title.x = element_blank(),
                                       axis.title.y = element_text(size = 14),
                                       legend.text = element_text(size = 16),
                                       legend.title = element_text(size = 16))
set_1_WS_bars <- set_1_WS_bars + scale_x_discrete(position = "bottom", expand = c(0,0))
set_1_WS_bars <- set_1_WS_bars + scale_y_continuous(expand = c(0,0), limits = c(0,700))
set_1_WS_bars <- set_1_WS_bars + geom_text(aes(x=isolate[24], y=640, label="205%"), hjust=0.38)
set_1_WS_bars <- set_1_WS_bars + geom_text(aes(x=isolate[11], y=600, label="187%"), hjust=0.38)
set_1_WS_bars

Wet Root

With NAs

# ggplot with bars
## remove control-WO
stat_set_1_WR_NAs <- filter(stat_set_1_WR, isolate != "control-WO")
## set the control value for Wet Root mg
set_1_WR_control_int <- as.numeric(stat_set_1_WR[58,5])
set_1_WR_bars_NA <- ggplot(stat_set_1_WR_NAs, aes(x = isolate, y = Average))
set_1_WR_bars_NA <- set_1_WR_bars_NA + geom_bar(stat = "identity", size=.5, fill="tan")
set_1_WR_bars_NA <- set_1_WR_bars_NA + geom_hline(aes(yintercept=set_1_WR_control_int), colour="#990000", linetype="dashed")
set_1_WR_bars_NA <- set_1_WR_bars_NA + labs(x="", y="Root - Fresh Weight (mg)")
set_1_WR_bars_NA <- set_1_WR_bars_NA + geom_errorbar(aes(ymin=Average-SE, ymax=Average+SE), size=.5, width=.2)
set_1_WR_bars_NA <- set_1_WR_bars_NA + theme(axis.text.x = element_text(angle = 75, hjust = 1, size = 12),
                                       axis.text.y = element_text(size = 12),
                                       axis.title.x = element_blank(),
                                       axis.title.y = element_text(size = 14),
                                       legend.text = element_text(size = 16),
                                       legend.title = element_text(size = 16))
set_1_WR_bars_NA <- set_1_WR_bars_NA + scale_x_discrete(position = "bottom", expand = c(0,0))
set_1_WR_bars_NA <- set_1_WR_bars_NA + scale_y_continuous(expand = c(0,0))
set_1_WR_bars_NA

Removed NAs

# ggplot with bars
## remove isoaltes with NA values
stat_s1_WR_complete <- stat_set_1_WR[complete.cases(stat_set_1_WR),]
## remove control-WO
stat_s1_WR_complete <- filter(stat_s1_WR_complete, isolate != "control-WO")
## set the control value for Wet Root mg
set_1_WR_control_int <- as.numeric(stat_s1_WR_complete[39,5])
## calculate % control for each treatment
stat_s1_WR_complete$control <- as.numeric(stat_s1_WR_complete[39,5])
stat_s1_WR_complete <- mutate(stat_s1_WR_complete, p_ctrl = (100* (Average / control)))
## Plot
set_1_WR_bars <- ggplot(stat_s1_WR_complete, aes(x = isolate, y = Average))
set_1_WR_bars <- set_1_WR_bars + geom_bar(stat = "identity", size=.5, fill="tan")
set_1_WR_bars <- set_1_WR_bars + geom_hline(aes(yintercept=set_1_WR_control_int), colour="#990000", linetype="dashed")
set_1_WR_bars <- set_1_WR_bars + labs(x="", y="Root - Fresh Weight (mg)")
set_1_WR_bars <- set_1_WR_bars + geom_errorbar(aes(ymin=Average-SE, ymax=Average+SE), size=.5, width=.2)
set_1_WR_bars <- set_1_WR_bars + theme(axis.text.x = element_text(angle = 60, hjust = 1, size = 12),
                                       axis.text.y = element_text(size = 12),
                                       axis.title.x = element_blank(),
                                       axis.title.y = element_text(size = 14),
                                       legend.text = element_text(size = 16),
                                       legend.title = element_text(size = 16))
set_1_WR_bars <- set_1_WR_bars + scale_x_discrete(position = "bottom", expand = c(0,0))
set_1_WR_bars <- set_1_WR_bars + scale_y_continuous(expand = c(0,0), limits = c(0,220))
set_1_WR_bars <- set_1_WR_bars + geom_text(aes(x=isolate[6], y=210, label="258%"), hjust=0.38)
set_1_WR_bars <- set_1_WR_bars + geom_text(aes(x=isolate[5], y=165, label="253%"), hjust=0.44)
set_1_WR_bars <- set_1_WR_bars + geom_text(aes(x=isolate[2], y=150, label="220%"), hjust=0.38)
set_1_WR_bars

Cowplot - Set 1 - NA’s Removed

set_1_wet_grid <- plot_grid(set_1_WS_bars + 
                                theme(plot.margin = unit(c(.1,.1,.1,.1), "cm")),
                            set_1_WR_bars + theme(plot.margin = unit(c(.1,.1,.1,.1), "cm")),
                            labels = c("A", "B"),
                            label_size = 24,
                            nrow = 2,
                            ncol = 1,
                            align = 'vh')
set_1_wet_grid

ggsave("./Plots/set_1_wet_grid.pdf", set_1_wet_grid, width = 16, height = 16)

Cowplot - Set 1 - With NA’s

set_1_wet_grid_NAs <- plot_grid(set_1_WS_bars_NA + theme(plot.margin = unit(c(.1,.1,.1,.1), "cm")),
                            set_1_WR_bars_NA + theme(plot.margin = unit(c(.1,.1,.1,.1), "cm")),
                            labels = c("A", "B"),
                            label_size = 24,
                            nrow = 2,
                            ncol = 1,
                            #vjust = 3,
                            align = 'vh')

Removed 12 rows containing missing values (position_stack).Removed 12 rows containing missing values (position_stack).

set_1_wet_grid_NAs

ggsave("./Plots/set_1_wet_grid_NAs.pdf", set_1_wet_grid_NAs, width = 16, height = 16)

Set 2.1

Wet Shoot

# ggplot with bars
## remove isoaltes with NA values
stat_s2.1_WS_complete <- stat_set_2.1_WS[complete.cases(stat_set_2.1_WS),]
## set the control value for Wet Shoot mg
set_2.1_WS_control_int <- as.numeric(stat_s2.1_WS_complete[31,5])
## calculate % control for each treatment
stat_s2.1_WS_complete$control <- as.numeric(stat_s2.1_WS_complete[31,5])
stat_s2.1_WS_complete <- mutate(stat_s2.1_WS_complete, p_ctrl = (100* (Average / control)))
set_2.1_WS_bars <- ggplot(stat_s2.1_WS_complete, aes(x = isolate, y = Average))
set_2.1_WS_bars <- set_2.1_WS_bars + geom_bar(stat = "identity", size=.5, fill="lightgreen")
set_2.1_WS_bars <- set_2.1_WS_bars + geom_hline(aes(yintercept=set_2.1_WS_control_int), colour="#990000", linetype="dashed")
set_2.1_WS_bars <- set_2.1_WS_bars + labs(x="", y="Shoot - Fresh Weight (mg)")
set_2.1_WS_bars <- set_2.1_WS_bars + geom_errorbar(aes(ymin=Average-SE, ymax=Average+SE), size=.5, width=.2)
set_2.1_WS_bars <- set_2.1_WS_bars + theme(axis.text.x = element_text(angle = 60, hjust = 1, size = 12),
                                       axis.text.y = element_text(size = 12),
                                       axis.title.x = element_blank(),
                                       axis.title.y = element_text(size = 14),
                                       legend.text = element_text(size = 16),
                                       legend.title = element_text(size = 16))
set_2.1_WS_bars <- set_2.1_WS_bars + scale_x_discrete(position = "bottom", expand = c(0,0))
set_2.1_WS_bars <- set_2.1_WS_bars + scale_y_continuous(expand = c(0,0), limits = c(0,700))
set_2.1_WS_bars <- set_2.1_WS_bars + geom_text(aes(x=isolate[12], y=590, label="301%"), hjust=0.38)
set_2.1_WS_bars

Wet Root

# ggplot with bars
## remove isoaltes with NA values
stat_s2.1_WR_complete <- stat_set_2.1_WR[complete.cases(stat_set_2.1_WR),]
## set the control value for Wet Root mg
set_2.1_WR_control_int <- as.numeric(stat_s2.1_WR_complete[31,5])
## calculate % control for each treatment
stat_s2.1_WR_complete$control <- as.numeric(stat_s2.1_WR_complete[31,5])
stat_s2.1_WR_complete <- mutate(stat_s2.1_WR_complete, p_ctrl = (100* (Average / control)))
set_2.1_WR_bars <- ggplot(stat_s2.1_WR_complete, aes(x = isolate, y = Average))
set_2.1_WR_bars <- set_2.1_WR_bars + geom_bar(stat = "identity", size=.5, fill="tan")
set_2.1_WR_bars <- set_2.1_WR_bars + geom_hline(aes(yintercept=set_2.1_WR_control_int), colour="#990000", linetype="dashed")
set_2.1_WR_bars <- set_2.1_WR_bars + labs(x="", y="Root - Fresh Weight (mg)")
set_2.1_WR_bars <- set_2.1_WR_bars + geom_errorbar(aes(ymin=Average-SE, ymax=Average+SE), size=.5, width=.2)
set_2.1_WR_bars <- set_2.1_WR_bars + theme(axis.text.x = element_text(angle = 60, hjust = 1, size = 12),
                                       axis.text.y = element_text(size = 12),
                                       axis.title.x = element_blank(),
                                       axis.title.y = element_text(size = 14),
                                       legend.text = element_text(size = 16),
                                       legend.title = element_text(size = 16))
set_2.1_WR_bars <- set_2.1_WR_bars + scale_x_discrete(position = "bottom", expand = c(0,0))
set_2.1_WR_bars <- set_2.1_WR_bars + scale_y_continuous(expand = c(0,0), limits = c(0,180))
set_2.1_WR_bars <- set_2.1_WR_bars + geom_text(aes(x=isolate[24], y=138, label="288%"), hjust=0.38)
set_2.1_WR_bars <- set_2.1_WR_bars + geom_text(aes(x=isolate[21], y=136, label="274%"), hjust=0.44)
set_2.1_WR_bars <- set_2.1_WR_bars + geom_text(aes(x=isolate[18], y=125, label="265%"), hjust=0.38)
set_2.1_WR_bars <- set_2.1_WR_bars + geom_text(aes(x=isolate[12], y=139.5, label="262%"), hjust=0.38)
set_2.1_WR_bars

Cowplot - Set 2.1

set_2.1_wet_grid <- plot_grid(set_2.1_WS_bars + 
                                theme(plot.margin = unit(c(.1,.1,.1,.1), "cm")),
                            set_2.1_WR_bars + theme(plot.margin = unit(c(.1,.1,.1,.1), "cm")),
                            labels = c("A", "B"),
                            label_size = 24,
                            nrow = 2,
                            ncol = 1,
                            align = 'vh')
set_2.1_wet_grid

ggsave("./Plots/set_2.1_wet_grid.pdf", set_2.1_wet_grid, width = 16, height = 16)

Set 2.2

Wet Shoot

# ggplot with bars
## remove isoaltes with NA values
stat_s2.2_WS_complete <- stat_set_2.2_WS[complete.cases(stat_set_2.2_WS),]
## set the control value for Wet Shoot mg
set_2.2_WS_control_int <- as.numeric(stat_s2.2_WS_complete[32,5])
## calculate % control for each treatment
stat_s2.2_WS_complete$control <- as.numeric(stat_s2.2_WS_complete[32,5])
stat_s2.2_WS_complete <- mutate(stat_s2.2_WS_complete, p_ctrl = (100* (Average / control)))
set_2.2_WS_bars <- ggplot(stat_s2.2_WS_complete, aes(x = isolate, y = Average))
set_2.2_WS_bars <- set_2.2_WS_bars + geom_bar(stat = "identity", size=.5, fill="lightgreen")
set_2.2_WS_bars <- set_2.2_WS_bars + geom_hline(aes(yintercept=set_2.2_WS_control_int), colour="#990000", linetype="dashed")
set_2.2_WS_bars <- set_2.2_WS_bars + labs(x="", y="Shoot - Fresh Weight (mg)")
set_2.2_WS_bars <- set_2.2_WS_bars + geom_errorbar(aes(ymin=Average-SE, ymax=Average+SE), size=.5, width=.2)
set_2.2_WS_bars <- set_2.2_WS_bars + theme(axis.text.x = element_text(angle = 60, hjust = 1, size = 12),
                                       axis.text.y = element_text(size = 12),
                                       axis.title.x = element_blank(),
                                       axis.title.y = element_text(size = 14),
                                       legend.text = element_text(size = 16),
                                       legend.title = element_text(size = 16))
set_2.2_WS_bars <- set_2.2_WS_bars + scale_x_discrete(position = "bottom", expand = c(0,0))
set_2.2_WS_bars <- set_2.2_WS_bars + scale_y_continuous(expand = c(0,0), limits = c(0,990))
set_2.2_WS_bars <- set_2.2_WS_bars + geom_text(aes(x=isolate[26], y=945, label="285%"), hjust=0.38)
set_2.2_WS_bars

Wet Root

# ggplot with bars
## remove isoaltes with NA values
stat_s2.2_WR_complete <- stat_set_2.2_WR[complete.cases(stat_set_2.2_WR),]
## set the control value for Wet Root mg
set_2.2_WR_control_int <- as.numeric(stat_s2.2_WR_complete[32,5])
## calculate % control for each treatment
stat_s2.2_WR_complete$control <- as.numeric(stat_s2.2_WR_complete[32,5])
stat_s2.2_WR_complete <- mutate(stat_s2.2_WR_complete, p_ctrl = (100* (Average / control)))
set_2.2_WR_bars <- ggplot(stat_s2.2_WR_complete, aes(x = isolate, y = Average))
set_2.2_WR_bars <- set_2.2_WR_bars + geom_bar(stat = "identity", size=.5, fill="tan")
set_2.2_WR_bars <- set_2.2_WR_bars + geom_hline(aes(yintercept=set_2.2_WR_control_int), colour="#990000", linetype="dashed")
set_2.2_WR_bars <- set_2.2_WR_bars + labs(x="", y="Root - Fresh Weight (mg)")
set_2.2_WR_bars <- set_2.2_WR_bars + geom_errorbar(aes(ymin=Average-SE, ymax=Average+SE), size=.5, width=.2)
set_2.2_WR_bars <- set_2.2_WR_bars + theme(axis.text.x = element_text(angle = 60, hjust = 1, size = 12),
                                       axis.text.y = element_text(size = 12),
                                       axis.title.x = element_blank(),
                                       axis.title.y = element_text(size = 14),
                                       legend.text = element_text(size = 16),
                                       legend.title = element_text(size = 16))
set_2.2_WR_bars <- set_2.2_WR_bars + scale_x_discrete(position = "bottom", expand = c(0,0))
set_2.2_WR_bars <- set_2.2_WR_bars + scale_y_continuous(expand = c(0,0), limits = c(0,180))
set_2.2_WR_bars <- set_2.2_WR_bars + geom_text(aes(x=isolate[26], y=170, label="226%"), hjust=0.38)
set_2.2_WR_bars

Cowplot - Set 2.2

set_2.2_wet_grid <- plot_grid(set_2.2_WS_bars + 
                                theme(plot.margin = unit(c(.1,.1,.1,.1), "cm")),
                            set_2.2_WR_bars + theme(plot.margin = unit(c(.1,.1,.1,.1), "cm")),
                            labels = c("A", "B"),
                            label_size = 24,
                            nrow = 2,
                            ncol = 1,
                            align = 'vh')
set_2.2_wet_grid

ggsave("./Plots/set_2.2_wet_grid.pdf", set_2.2_wet_grid, width = 16, height = 16)

Set 2.3

Wet Shoot

# ggplot with bars
## remove isoaltes with NA values
stat_s2.3_WS_complete <- stat_set_2.3_WS[complete.cases(stat_set_2.3_WS),]
## set the control value for Wet Shoot mg
set_2.3_WS_control_int <- as.numeric(stat_s2.3_WS_complete[25,5])
## calculate % control for each treatment
stat_s2.3_WS_complete$control <- as.numeric(stat_s2.3_WS_complete[25,5])
stat_s2.3_WS_complete <- mutate(stat_s2.3_WS_complete, p_ctrl = (100* (Average / control)))
set_2.3_WS_bars <- ggplot(stat_s2.3_WS_complete, aes(x = isolate, y = Average))
set_2.3_WS_bars <- set_2.3_WS_bars + geom_bar(stat = "identity", size=.5, fill="lightgreen")
set_2.3_WS_bars <- set_2.3_WS_bars + geom_hline(aes(yintercept=set_2.3_WS_control_int), colour="#990000", linetype="dashed")
set_2.3_WS_bars <- set_2.3_WS_bars + labs(x="", y="Shoot - Fresh Weight (mg)")
set_2.3_WS_bars <- set_2.3_WS_bars + geom_errorbar(aes(ymin=Average-SE, ymax=Average+SE), size=.5, width=.2)
set_2.3_WS_bars <- set_2.3_WS_bars + theme(axis.text.x = element_text(angle = 60, hjust = 1, size = 12),
                                       axis.text.y = element_text(size = 12),
                                       axis.title.x = element_blank(),
                                       axis.title.y = element_text(size = 14),
                                       legend.text = element_text(size = 16),
                                       legend.title = element_text(size = 16))
set_2.3_WS_bars <- set_2.3_WS_bars + scale_x_discrete(position = "bottom", expand = c(0,0))
set_2.3_WS_bars <- set_2.3_WS_bars + scale_y_continuous(expand = c(0,0))
set_2.3_WS_bars <- set_2.3_WS_bars + geom_text(aes(x=1, y=650, label="Stretch it"), vjust=-1)
set_2.3_WS_bars

Wet Root

# ggplot with bars
## remove isoaltes with NA values
stat_s2.3_WR_complete <- stat_set_2.3_WR[complete.cases(stat_set_2.3_WR),]
## set the control value for Wet Root mg
set_2.3_WR_control_int <- as.numeric(stat_s2.3_WR_complete[25,5])
## calculate % control for each treatment
stat_s2.3_WR_complete$control <- as.numeric(stat_s2.3_WR_complete[25,5])
stat_s2.3_WR_complete <- mutate(stat_s2.3_WR_complete, p_ctrl = (100* (Average / control)))
set_2.3_WR_bars <- ggplot(stat_s2.3_WR_complete, aes(x = isolate, y = Average))
set_2.3_WR_bars <- set_2.3_WR_bars + geom_bar(stat = "identity", size=.5, fill="tan")
set_2.3_WR_bars <- set_2.3_WR_bars + geom_hline(aes(yintercept=set_2.3_WR_control_int), colour="#990000", linetype="dashed")
set_2.3_WR_bars <- set_2.3_WR_bars + labs(x="", y="Root - Fresh Weight (mg)")
set_2.3_WR_bars <- set_2.3_WR_bars + geom_errorbar(aes(ymin=Average-SE, ymax=Average+SE), size=.5, width=.2)
set_2.3_WR_bars <- set_2.3_WR_bars + theme(axis.text.x = element_text(angle = 60, hjust = 1, size = 12),
                                       axis.text.y = element_text(size = 12),
                                       axis.title.x = element_blank(),
                                       axis.title.y = element_text(size = 14),
                                       legend.text = element_text(size = 16),
                                       legend.title = element_text(size = 16))
set_2.3_WR_bars <- set_2.3_WR_bars + scale_x_discrete(position = "bottom", expand = c(0,0))
set_2.3_WR_bars <- set_2.3_WR_bars + scale_y_continuous(expand = c(0,0))
set_2.3_WR_bars <- set_2.3_WR_bars + geom_text(aes(x=1, y=195, label=""), vjust=-1)
set_2.3_WR_bars

Cowplot - Set 2.3

set_2.3_wet_grid <- plot_grid(set_2.3_WS_bars + 
                                theme(plot.margin = unit(c(.1,.1,.1,.1), "cm")),
                            set_2.3_WR_bars + theme(plot.margin = unit(c(.1,.1,.1,.1), "cm")),
                            labels = c("A", "B"),
                            label_size = 24,
                            nrow = 2,
                            ncol = 1,
                            align = 'vh')
set_2.3_wet_grid

ggsave("./Plots/set_2.3_wet_grid.pdf", set_2.3_wet_grid, width = 16, height = 16)

Set 2.4

Wet Shoot

# ggplot with bars
## remove isoaltes with NA values
stat_s2.4_WS_complete <- stat_set_2.4_WS[complete.cases(stat_set_2.4_WS),]
## set the control value for Wet Shoot mg
set_2.4_WS_control_int <- as.numeric(stat_s2.4_WS_complete[36,5])
## calculate % control for each treatment
stat_s2.4_WS_complete$control <- as.numeric(stat_s2.4_WS_complete[36,5])
stat_s2.4_WS_complete <- mutate(stat_s2.4_WS_complete, p_ctrl = (100* (Average / control)))
set_2.4_WS_bars <- ggplot(stat_s2.4_WS_complete, aes(x = isolate, y = Average))
set_2.4_WS_bars <- set_2.4_WS_bars + geom_bar(stat = "identity", size=.5, fill="lightgreen")
set_2.4_WS_bars <- set_2.4_WS_bars + geom_hline(aes(yintercept=set_2.4_WS_control_int), colour="#990000", linetype="dashed")
set_2.4_WS_bars <- set_2.4_WS_bars + labs(x="", y="Shoot - Fresh Weight (mg)")
set_2.4_WS_bars <- set_2.4_WS_bars + geom_errorbar(aes(ymin=Average-SE, ymax=Average+SE), size=.5, width=.2)
set_2.4_WS_bars <- set_2.4_WS_bars + theme(axis.text.x = element_text(angle = 60, hjust = 1, size = 12),
                                       axis.text.y = element_text(size = 12),
                                       axis.title.x = element_blank(),
                                       axis.title.y = element_text(size = 14),
                                       legend.text = element_text(size = 16),
                                       legend.title = element_text(size = 16))
set_2.4_WS_bars <- set_2.4_WS_bars + scale_x_discrete(position = "bottom", expand = c(0,0))
set_2.4_WS_bars <- set_2.4_WS_bars + scale_y_continuous(expand = c(0,0), limits = c(0,775))
set_2.4_WS_bars <- set_2.4_WS_bars + geom_text(aes(x=isolate[34], y=735, label="256%"), hjust=0.38)
set_2.4_WS_bars <- set_2.4_WS_bars + geom_text(aes(x=isolate[25], y=636, label="197%"), hjust=0.38)
set_2.4_WS_bars

Wet Root

# ggplot with bars
## remove isoaltes with NA values
stat_s2.4_WR_complete <- stat_set_2.4_WR[complete.cases(stat_set_2.4_WR),]
## set the control value for Wet Root mg
set_2.4_WR_control_int <- as.numeric(stat_s2.4_WR_complete[36,5])
## calculate % control for each treatment
stat_s2.4_WR_complete$control <- as.numeric(stat_s2.4_WR_complete[36,5])
stat_s2.4_WR_complete <- mutate(stat_s2.4_WR_complete, p_ctrl = (100* (Average / control)))
set_2.4_WR_bars <- ggplot(stat_s2.4_WR_complete, aes(x = isolate, y = Average))
set_2.4_WR_bars <- set_2.4_WR_bars + geom_bar(stat = "identity", size=.5, fill="tan")
set_2.4_WR_bars <- set_2.4_WR_bars + geom_hline(aes(yintercept=set_2.4_WR_control_int), colour="#990000", linetype="dashed")
set_2.4_WR_bars <- set_2.4_WR_bars + labs(x="", y="Root - Fresh Weight (mg)")
set_2.4_WR_bars <- set_2.4_WR_bars + geom_errorbar(aes(ymin=Average-SE, ymax=Average+SE), size=.5, width=.2)
set_2.4_WR_bars <- set_2.4_WR_bars + theme(axis.text.x = element_text(angle = 60, hjust = 1, size = 12),
                                       axis.text.y = element_text(size = 12),
                                       axis.title.x = element_blank(),
                                       axis.title.y = element_text(size = 14),
                                       legend.text = element_text(size = 16),
                                       legend.title = element_text(size = 16))
set_2.4_WR_bars <- set_2.4_WR_bars + scale_x_discrete(position = "bottom", expand = c(0,0))
set_2.4_WR_bars <- set_2.4_WR_bars + scale_y_continuous(expand = c(0,0), limits = c(0,175))
set_2.4_WR_bars <- set_2.4_WR_bars + geom_text(aes(x=isolate[34], y=165, label="293%"), hjust=0.38)
set_2.4_WR_bars

Cowplot - Set 2.4

set_2.4_wet_grid <- plot_grid(set_2.4_WS_bars + 
                                theme(plot.margin = unit(c(.1,.1,.1,.1), "cm")),
                            set_2.4_WR_bars + theme(plot.margin = unit(c(.1,.1,.1,.1), "cm")),
                            labels = c("A", "B"),
                            label_size = 24,
                            nrow = 2,
                            ncol = 1,
                            align = 'vh')
set_2.4_wet_grid

ggsave("./Plots/set_2.4_wet_grid.pdf", set_2.4_wet_grid, width = 16, height = 16)

Set 3.1

Wet Shoot

# ggplot with bars
## remove isoaltes with NA values
stat_s3.1_WS_complete <- stat_set_3.1_WS[complete.cases(stat_set_3.1_WS),]
## set the control value for Wet Shoot mg
set_3.1_WS_control_int <- as.numeric(stat_s3.1_WS_complete[36,5])
## calculate % control for each treatment
stat_s3.1_WS_complete$control <- as.numeric(stat_s3.1_WS_complete[36,5])
stat_s3.1_WS_complete <- mutate(stat_s3.1_WS_complete, p_ctrl = (100* (Average / control)))
set_3.1_WS_bars <- ggplot(stat_s3.1_WS_complete, aes(x = isolate, y = Average))
set_3.1_WS_bars <- set_3.1_WS_bars + geom_bar(stat = "identity", size=.5, fill="lightgreen")
set_3.1_WS_bars <- set_3.1_WS_bars + geom_hline(aes(yintercept=set_3.1_WS_control_int), colour="#990000", linetype="dashed")
set_3.1_WS_bars <- set_3.1_WS_bars + labs(x="", y="Shoot - Fresh Weight (mg)")
set_3.1_WS_bars <- set_3.1_WS_bars + geom_errorbar(aes(ymin=Average-SE, ymax=Average+SE), size=.5, width=.2)
set_3.1_WS_bars <- set_3.1_WS_bars + theme(axis.text.x = element_text(angle = 60, hjust = 1, size = 12),
                                       axis.text.y = element_text(size = 12),
                                       axis.title.x = element_blank(),
                                       axis.title.y = element_text(size = 14),
                                       legend.text = element_text(size = 16),
                                       legend.title = element_text(size = 16))
set_3.1_WS_bars <- set_3.1_WS_bars + scale_x_discrete(position = "bottom", expand = c(0,0))
set_3.1_WS_bars <- set_3.1_WS_bars + scale_y_continuous(expand = c(0,0), limits = c(0,900))
set_3.1_WS_bars <- set_3.1_WS_bars + geom_text(aes(x=isolate[18], y=814, label="233%"), hjust=0.38)
set_3.1_WS_bars <- set_3.1_WS_bars + geom_text(aes(x=isolate[33], y=564, label="223%"), hjust=0.38)
set_3.1_WS_bars

Wet Root

# ggplot with bars
## remove isoaltes with NA values
stat_s3.1_WR_complete <- stat_set_3.1_WR[complete.cases(stat_set_3.1_WR),]
## set the control value for Wet Root mg
set_3.1_WR_control_int <- as.numeric(stat_s3.1_WR_complete[36,5])
## calculate % control for each treatment
stat_s3.1_WR_complete$control <- as.numeric(stat_s3.1_WR_complete[36,5])
stat_s3.1_WR_complete <- mutate(stat_s3.1_WR_complete, p_ctrl = (100* (Average / control)))
set_3.1_WR_bars <- ggplot(stat_s3.1_WR_complete, aes(x = isolate, y = Average))
set_3.1_WR_bars <- set_3.1_WR_bars + geom_bar(stat = "identity", size=.5, fill="tan")
set_3.1_WR_bars <- set_3.1_WR_bars + geom_hline(aes(yintercept=set_3.1_WR_control_int), colour="#990000", linetype="dashed")
set_3.1_WR_bars <- set_3.1_WR_bars + labs(x="", y="Root - Fresh Weight (mg)")
set_3.1_WR_bars <- set_3.1_WR_bars + geom_errorbar(aes(ymin=Average-SE, ymax=Average+SE), size=.5, width=.2)
set_3.1_WR_bars <- set_3.1_WR_bars + theme(axis.text.x = element_text(angle = 60, hjust = 1, size = 12),
                                       axis.text.y = element_text(size = 12),
                                       axis.title.x = element_blank(),
                                       axis.title.y = element_text(size = 14),
                                       legend.text = element_text(size = 16),
                                       legend.title = element_text(size = 16))
set_3.1_WR_bars <- set_3.1_WR_bars + scale_x_discrete(position = "bottom", expand = c(0,0))
set_3.1_WR_bars <- set_3.1_WR_bars + scale_y_continuous(expand = c(0,0), limits = c(0,145))
set_3.1_WR_bars <- set_3.1_WR_bars + geom_text(aes(x=isolate[18], y=132, label="194%"), hjust=0.38)
set_3.1_WR_bars

Cowplot - Set 3.1

set_3.1_wet_grid <- plot_grid(set_3.1_WS_bars + 
                                theme(plot.margin = unit(c(.1,.1,.1,.1), "cm")),
                            set_3.1_WR_bars + theme(plot.margin = unit(c(.1,.1,.1,.1), "cm")),
                            labels = c("A", "B"),
                            label_size = 24,
                            nrow = 2,
                            ncol = 1,
                            align = 'vh')
set_3.1_wet_grid

ggsave("./Plots/set_3.1_wet_grid.pdf", set_3.1_wet_grid, width = 16, height = 16)

Set 3.2

Wet Shoot

# ggplot with bars
## remove isoaltes with NA values
stat_s3.2_WS_complete <- stat_set_3.2_WS[complete.cases(stat_set_3.2_WS),]
## set the control value for Wet Shoot mg
set_3.2_WS_control_int <- as.numeric(stat_s3.2_WS_complete[24,5])
## calculate % control for each treatment
stat_s3.2_WS_complete$control <- as.numeric(stat_s3.2_WS_complete[24,5])
stat_s3.2_WS_complete <- mutate(stat_s3.2_WS_complete, p_ctrl = (100* (Average / control)))
set_3.2_WS_bars <- ggplot(stat_s3.2_WS_complete, aes(x = isolate, y = Average))
set_3.2_WS_bars <- set_3.2_WS_bars + geom_bar(stat = "identity", size=.5, fill="lightgreen")
set_3.2_WS_bars <- set_3.2_WS_bars + geom_hline(aes(yintercept=set_3.2_WS_control_int), colour="#990000", linetype="dashed")
set_3.2_WS_bars <- set_3.2_WS_bars + labs(x="", y="Shoot - Fresh Weight (mg)")
set_3.2_WS_bars <- set_3.2_WS_bars + geom_errorbar(aes(ymin=Average-SE, ymax=Average+SE), size=.5, width=.2)
set_3.2_WS_bars <- set_3.2_WS_bars + theme(axis.text.x = element_text(angle = 60, hjust = 1, size = 12),
                                       axis.text.y = element_text(size = 12),
                                       axis.title.x = element_blank(),
                                       axis.title.y = element_text(size = 14),
                                       legend.text = element_text(size = 16),
                                       legend.title = element_text(size = 16))
set_3.2_WS_bars <- set_3.2_WS_bars + scale_x_discrete(position = "bottom", expand = c(0,0))
set_3.2_WS_bars <- set_3.2_WS_bars + scale_y_continuous(expand = c(0,0))
set_3.2_WS_bars <- set_3.2_WS_bars + geom_text(aes(x=1, y=560, label="Stretch it"), vjust=-1)
set_3.2_WS_bars

Wet Root

# ggplot with bars
## remove isoaltes with NA values
stat_s3.2_WR_complete <- stat_set_3.2_WR[complete.cases(stat_set_3.2_WR),]
## set the control value for Wet Root mg
set_3.2_WR_control_int <- as.numeric(stat_s3.2_WR_complete[24,5])
## calculate % control for each treatment
stat_s3.2_WR_complete$control <- as.numeric(stat_s3.2_WR_complete[24,5])
stat_s3.2_WR_complete <- mutate(stat_s3.2_WR_complete, p_ctrl = (100* (Average / control)))
set_3.2_WR_bars <- ggplot(stat_s3.2_WR_complete, aes(x = isolate, y = Average))
set_3.2_WR_bars <- set_3.2_WR_bars + geom_bar(stat = "identity", size=.5, fill="tan")
set_3.2_WR_bars <- set_3.2_WR_bars + geom_hline(aes(yintercept=set_3.2_WR_control_int), colour="#990000", linetype="dashed")
set_3.2_WR_bars <- set_3.2_WR_bars + labs(x="", y="Root - Fresh Weight (mg)")
set_3.2_WR_bars <- set_3.2_WR_bars + geom_errorbar(aes(ymin=Average-SE, ymax=Average+SE), size=.5, width=.2)
set_3.2_WR_bars <- set_3.2_WR_bars + theme(axis.text.x = element_text(angle = 60, hjust = 1, size = 12),
                                       axis.text.y = element_text(size = 12),
                                       axis.title.x = element_blank(),
                                       axis.title.y = element_text(size = 14),
                                       legend.text = element_text(size = 16),
                                       legend.title = element_text(size = 16))
set_3.2_WR_bars <- set_3.2_WR_bars + scale_x_discrete(position = "bottom", expand = c(0,0))
set_3.2_WR_bars <- set_3.2_WR_bars + scale_y_continuous(expand = c(0,0))
set_3.2_WR_bars <- set_3.2_WR_bars + geom_text(aes(x=1, y=95, label=""), vjust=-1)
set_3.2_WR_bars

Cowplot - Set 3.2

set_3.2_wet_grid <- plot_grid(set_3.2_WS_bars + 
                                theme(plot.margin = unit(c(.1,.1,.1,.1), "cm")),
                            set_3.2_WR_bars + theme(plot.margin = unit(c(.1,.1,.1,.1), "cm")),
                            labels = c("A", "B"),
                            label_size = 24,
                            nrow = 2,
                            ncol = 1,
                            align = 'vh')
set_3.2_wet_grid

ggsave("./Plots/set_3.2_wet_grid.pdf", set_3.2_wet_grid, width = 16, height = 16)

Set 3.3

Wet Shoot

# ggplot with bars
## remove isoaltes with NA values
stat_s3.3_WS_complete <- stat_set_3.3_WS[complete.cases(stat_set_3.3_WS),]
## set the control value for Wet Shoot mg
set_3.3_WS_control_int <- as.numeric(stat_s3.3_WS_complete[37,5])
## calculate % control for each treatment
stat_s3.3_WS_complete$control <- as.numeric(stat_s3.3_WS_complete[37,5])
stat_s3.3_WS_complete <- mutate(stat_s3.3_WS_complete, p_ctrl = (100* (Average / control)))
set_3.3_WS_bars <- ggplot(stat_s3.3_WS_complete, aes(x = isolate, y = Average))
set_3.3_WS_bars <- set_3.3_WS_bars + geom_bar(stat = "identity", size=.5, fill="lightgreen")
set_3.3_WS_bars <- set_3.3_WS_bars + geom_hline(aes(yintercept=set_3.3_WS_control_int), colour="#990000", linetype="dashed")
set_3.3_WS_bars <- set_3.3_WS_bars + labs(x="", y="Shoot - Fresh Weight (mg)")
set_3.3_WS_bars <- set_3.3_WS_bars + geom_errorbar(aes(ymin=Average-SE, ymax=Average+SE), size=.5, width=.2)
set_3.3_WS_bars <- set_3.3_WS_bars + theme(axis.text.x = element_text(angle = 60, hjust = 1, size = 12),
                                       axis.text.y = element_text(size = 12),
                                       axis.title.x = element_blank(),
                                       axis.title.y = element_text(size = 14),
                                       legend.text = element_text(size = 16),
                                       legend.title = element_text(size = 16))
set_3.3_WS_bars <- set_3.3_WS_bars + scale_x_discrete(position = "bottom", expand = c(0,0))
set_3.3_WS_bars <- set_3.3_WS_bars + scale_y_continuous(expand = c(0,0))
set_3.3_WS_bars <- set_3.3_WS_bars + geom_text(aes(x=1, y=990, label=""), vjust=-1)
set_3.3_WS_bars

Wet Root

# ggplot with bars
## remove isoaltes with NA values
stat_s3.3_WR_complete <- stat_set_3.3_WR[complete.cases(stat_set_3.3_WR),]
## set the control value for Wet Root mg
set_3.3_WR_control_int <- as.numeric(stat_s3.3_WR_complete[37,5])
## calculate % control for each treatment
stat_s3.3_WR_complete$control <- as.numeric(stat_s3.3_WR_complete[37,5])
stat_s3.3_WR_complete <- mutate(stat_s3.3_WR_complete, p_ctrl = (100* (Average / control)))
set_3.3_WR_bars <- ggplot(stat_s3.3_WR_complete, aes(x = isolate, y = Average))
set_3.3_WR_bars <- set_3.3_WR_bars + geom_bar(stat = "identity", size=.5, fill="tan")
set_3.3_WR_bars <- set_3.3_WR_bars + geom_hline(aes(yintercept=set_3.3_WR_control_int), colour="#990000", linetype="dashed")
set_3.3_WR_bars <- set_3.3_WR_bars + labs(x="", y="Root - Fresh Weight (mg)")
set_3.3_WR_bars <- set_3.3_WR_bars + geom_errorbar(aes(ymin=Average-SE, ymax=Average+SE), size=.5, width=.2)
set_3.3_WR_bars <- set_3.3_WR_bars + theme(axis.text.x = element_text(angle = 60, hjust = 1, size = 12),
                                       axis.text.y = element_text(size = 12),
                                       axis.title.x = element_blank(),
                                       axis.title.y = element_text(size = 14),
                                       legend.text = element_text(size = 16),
                                       legend.title = element_text(size = 16))
set_3.3_WR_bars <- set_3.3_WR_bars + scale_x_discrete(position = "bottom", expand = c(0,0))
set_3.3_WR_bars <- set_3.3_WR_bars + scale_y_continuous(expand = c(0,0))
set_3.3_WR_bars <- set_3.3_WR_bars + geom_text(aes(x=1, y=175, label=""), vjust=-1)
set_3.3_WR_bars

Cowplot - Set 3.3

set_3.3_wet_grid <- plot_grid(set_3.3_WS_bars + 
                                theme(plot.margin = unit(c(.1,.1,.1,.1), "cm")),
                            set_3.3_WR_bars + theme(plot.margin = unit(c(.1,.1,.1,.1), "cm")),
                            labels = c("A", "B"),
                            label_size = 24,
                            nrow = 2,
                            ncol = 1,
                            align = 'vh')
set_3.3_wet_grid

ggsave("./Plots/set_3.3_wet_grid.pdf", set_3.3_wet_grid, width = 16, height = 16)

Set 3.4

Wet Shoot

# ggplot with bars
## remove isoaltes with NA values
stat_s3.4_WS_complete <- stat_set_3.4_WS[complete.cases(stat_set_3.4_WS),]
## set the control value for Wet Shoot mg
set_3.4_WS_control_int <- as.numeric(stat_s3.4_WS_complete[36,5])
## calculate % control for each treatment
stat_s3.4_WS_complete$control <- as.numeric(stat_s3.4_WS_complete[36,5])
stat_s3.4_WS_complete <- mutate(stat_s3.4_WS_complete, p_ctrl = (100* (Average / control)))
set_3.4_WS_bars <- ggplot(stat_s3.4_WS_complete, aes(x = isolate, y = Average))
set_3.4_WS_bars <- set_3.4_WS_bars + geom_bar(stat = "identity", size=.5, fill="lightgreen")
set_3.4_WS_bars <- set_3.4_WS_bars + geom_hline(aes(yintercept=set_3.4_WS_control_int), colour="#990000", linetype="dashed")
set_3.4_WS_bars <- set_3.4_WS_bars + labs(x="", y="Shoot - Fresh Weight (mg)")
set_3.4_WS_bars <- set_3.4_WS_bars + geom_errorbar(aes(ymin=Average-SE, ymax=Average+SE), size=.5, width=.2)
set_3.4_WS_bars <- set_3.4_WS_bars + theme(axis.text.x = element_text(angle = 60, hjust = 1, size = 12),
                                       axis.text.y = element_text(size = 12),
                                       axis.title.x = element_blank(),
                                       axis.title.y = element_text(size = 14),
                                       legend.text = element_text(size = 16),
                                       legend.title = element_text(size = 16))
set_3.4_WS_bars <- set_3.4_WS_bars + scale_x_discrete(position = "bottom", expand = c(0,0))
set_3.4_WS_bars <- set_3.4_WS_bars + scale_y_continuous(expand = c(0,0))
set_3.4_WS_bars <- set_3.4_WS_bars + geom_text(aes(x=1, y=580, label="Stretch it"), vjust=-1)
set_3.4_WS_bars

Wet Root

# ggplot with bars
## remove isoaltes with NA values
stat_s3.4_WR_complete <- stat_set_3.4_WR[complete.cases(stat_set_3.4_WR),]
## set the control value for Wet Root mg
set_3.4_WR_control_int <- as.numeric(stat_s3.4_WR_complete[36,5])
## calculate % control for each treatment
stat_s3.4_WR_complete$control <- as.numeric(stat_s3.4_WR_complete[36,5])
stat_s3.4_WR_complete <- mutate(stat_s3.4_WR_complete, p_ctrl = (100* (Average / control)))
set_3.4_WR_bars <- ggplot(stat_s3.4_WR_complete, aes(x = isolate, y = Average))
set_3.4_WR_bars <- set_3.4_WR_bars + geom_bar(stat = "identity", size=.5, fill="tan")
set_3.4_WR_bars <- set_3.4_WR_bars + geom_hline(aes(yintercept=set_3.4_WR_control_int), colour="#990000", linetype="dashed")
set_3.4_WR_bars <- set_3.4_WR_bars + labs(x="", y="Root - Fresh Weight (mg)")
set_3.4_WR_bars <- set_3.4_WR_bars + geom_errorbar(aes(ymin=Average-SE, ymax=Average+SE), size=.5, width=.2)
set_3.4_WR_bars <- set_3.4_WR_bars + theme(axis.text.x = element_text(angle = 60, hjust = 1, size = 12),
                                       axis.text.y = element_text(size = 12),
                                       axis.title.x = element_blank(),
                                       axis.title.y = element_text(size = 14),
                                       legend.text = element_text(size = 16),
                                       legend.title = element_text(size = 16))
set_3.4_WR_bars <- set_3.4_WR_bars + scale_x_discrete(position = "bottom", expand = c(0,0))
set_3.4_WR_bars <- set_3.4_WR_bars + scale_y_continuous(expand = c(0,0))
set_3.4_WR_bars <- set_3.4_WR_bars + geom_text(aes(x=1, y=90, label=""), vjust=-1)
set_3.4_WR_bars

Cowplot - Set 3.4

set_3.4_wet_grid <- plot_grid(set_3.4_WS_bars + 
                                theme(plot.margin = unit(c(.1,.1,.1,.1), "cm")),
                            set_3.4_WR_bars + theme(plot.margin = unit(c(.1,.1,.1,.1), "cm")),
                            labels = c("A", "B"),
                            label_size = 24,
                            nrow = 2,
                            ncol = 1,
                            align = 'vh')
set_3.4_wet_grid

ggsave("./Plots/set_3.4_wet_grid.pdf", set_3.4_wet_grid, width = 16, height = 16)

Set 3.5

Wet Shoot

# ggplot with bars
## remove isoaltes with NA values
stat_s3.5_WS_complete <- stat_set_3.5_WS[complete.cases(stat_set_3.5_WS),]
## set the control value for Wet Shoot mg
set_3.5_WS_control_int <- as.numeric(stat_s3.5_WS_complete[20,5])
## calculate % control for each treatment
stat_s3.5_WS_complete$control <- as.numeric(stat_s3.5_WS_complete[20,5])
stat_s3.5_WS_complete <- mutate(stat_s3.5_WS_complete, p_ctrl = (100* (Average / control)))
set_3.5_WS_bars <- ggplot(stat_s3.5_WS_complete, aes(x = isolate, y = Average))
set_3.5_WS_bars <- set_3.5_WS_bars + geom_bar(stat = "identity", size=.5, fill="lightgreen")
set_3.5_WS_bars <- set_3.5_WS_bars + geom_hline(aes(yintercept=set_3.5_WS_control_int), colour="#990000", linetype="dashed")
set_3.5_WS_bars <- set_3.5_WS_bars + labs(x="", y="Shoot - Fresh Weight (mg)")
set_3.5_WS_bars <- set_3.5_WS_bars + geom_errorbar(aes(ymin=Average-SE, ymax=Average+SE), size=.5, width=.2)
set_3.5_WS_bars <- set_3.5_WS_bars + theme(axis.text.x = element_text(angle = 60, hjust = 1, size = 12),
                                       axis.text.y = element_text(size = 12),
                                       axis.title.x = element_blank(),
                                       axis.title.y = element_text(size = 14),
                                       legend.text = element_text(size = 16),
                                       legend.title = element_text(size = 16))
set_3.5_WS_bars <- set_3.5_WS_bars + scale_x_discrete(position = "bottom", expand = c(0,0))
set_3.5_WS_bars <- set_3.5_WS_bars + scale_y_continuous(expand = c(0,0))
set_3.5_WS_bars <- set_3.5_WS_bars + geom_text(aes(x=1, y=580, label="Stretch it"), vjust=-1)
set_3.5_WS_bars

Wet Root

# ggplot with bars
## remove isoaltes with NA values
stat_s3.5_WR_complete <- stat_set_3.5_WR[complete.cases(stat_set_3.5_WR),]
## set the control value for Wet Root mg
set_3.5_WR_control_int <- as.numeric(stat_s3.5_WR_complete[20,5])
## calculate % control for each treatment
stat_s3.5_WR_complete$control <- as.numeric(stat_s3.5_WR_complete[20,5])
stat_s3.5_WR_complete <- mutate(stat_s3.5_WR_complete, p_ctrl = (100* (Average / control)))
set_3.5_WR_bars <- ggplot(stat_s3.5_WR_complete, aes(x = isolate, y = Average))
set_3.5_WR_bars <- set_3.5_WR_bars + geom_bar(stat = "identity", size=.5, fill="tan")
set_3.5_WR_bars <- set_3.5_WR_bars + geom_hline(aes(yintercept=set_3.5_WR_control_int), colour="#990000", linetype="dashed")
set_3.5_WR_bars <- set_3.5_WR_bars + labs(x="", y="Root - Fresh Weight (mg)")
set_3.5_WR_bars <- set_3.5_WR_bars + geom_errorbar(aes(ymin=Average-SE, ymax=Average+SE), size=.5, width=.2)
set_3.5_WR_bars <- set_3.5_WR_bars + theme(axis.text.x = element_text(angle = 60, hjust = 1, size = 12),
                                       axis.text.y = element_text(size = 12),
                                       axis.title.x = element_blank(),
                                       axis.title.y = element_text(size = 14),
                                       legend.text = element_text(size = 16),
                                       legend.title = element_text(size = 16))
set_3.5_WR_bars <- set_3.5_WR_bars + scale_x_discrete(position = "bottom", expand = c(0,0))
set_3.5_WR_bars <- set_3.5_WR_bars + scale_y_continuous(expand = c(0,0))
set_3.5_WR_bars <- set_3.5_WR_bars + geom_text(aes(x=1, y=99, label=""), vjust=-1)
set_3.5_WR_bars

Cowplot - Set 3.5

set_3.5_wet_grid <- plot_grid(set_3.5_WS_bars + 
                                theme(plot.margin = unit(c(.1,.1,.1,.1), "cm")),
                            set_3.5_WR_bars + theme(plot.margin = unit(c(.1,.1,.1,.1), "cm")),
                            labels = c("A", "B"),
                            label_size = 24,
                            nrow = 2,
                            ncol = 1,
                            align = 'vh')
set_3.5_wet_grid

ggsave("./Plots/set_3.5_wet_grid.pdf", set_3.5_wet_grid, width = 16, height = 16)

Set 4.1

Wet Shoot

# ggplot with bars
## remove isoaltes with NA values
stat_s4.1_WS_complete <- stat_set_4.1_WS[complete.cases(stat_set_4.1_WS),]
## set the control value for Wet Shoot mg
set_4.1_WS_control_int <- as.numeric(stat_s4.1_WS_complete[37,5])
## calculate % control for each treatment
stat_s4.1_WS_complete$control <- as.numeric(stat_s4.1_WS_complete[37,5])
stat_s4.1_WS_complete <- mutate(stat_s4.1_WS_complete, p_ctrl = (100* (Average / control)))
set_4.1_WS_bars <- ggplot(stat_s4.1_WS_complete, aes(x = isolate, y = Average))
set_4.1_WS_bars <- set_4.1_WS_bars + geom_bar(stat = "identity", size=.5, fill="lightgreen")
set_4.1_WS_bars <- set_4.1_WS_bars + geom_hline(aes(yintercept=set_4.1_WS_control_int), colour="#990000", linetype="dashed")
set_4.1_WS_bars <- set_4.1_WS_bars + labs(x="", y="Shoot - Fresh Weight (mg)")
set_4.1_WS_bars <- set_4.1_WS_bars + geom_errorbar(aes(ymin=Average-SE, ymax=Average+SE), size=.5, width=.2)
set_4.1_WS_bars <- set_4.1_WS_bars + theme(axis.text.x = element_text(angle = 60, hjust = 1, size = 12),
                                       axis.text.y = element_text(size = 12),
                                       axis.title.x = element_blank(),
                                       axis.title.y = element_text(size = 14),
                                       legend.text = element_text(size = 16),
                                       legend.title = element_text(size = 16))
set_4.1_WS_bars <- set_4.1_WS_bars + scale_x_discrete(position = "bottom", expand = c(0,0))
set_4.1_WS_bars <- set_4.1_WS_bars + scale_y_continuous(expand = c(0,0), limits = c(0,750))
set_4.1_WS_bars <- set_4.1_WS_bars + geom_text(aes(x=isolate[25], y=680, label="189%"), hjust=0.38)
set_4.1_WS_bars

Wet Root

# ggplot with bars
## remove isoaltes with NA values
stat_s4.1_WR_complete <- stat_set_4.1_WR[complete.cases(stat_set_4.1_WR),]
## set the control value for Wet Root mg
set_4.1_WR_control_int <- as.numeric(stat_s4.1_WR_complete[37,5])
## calculate % control for each treatment
stat_s4.1_WR_complete$control <- as.numeric(stat_s4.1_WR_complete[37,5])
stat_s4.1_WR_complete <- mutate(stat_s4.1_WR_complete, p_ctrl = (100* (Average / control)))
set_4.1_WR_bars <- ggplot(stat_s4.1_WR_complete, aes(x = isolate, y = Average))
set_4.1_WR_bars <- set_4.1_WR_bars + geom_bar(stat = "identity", size=.5, fill="tan")
set_4.1_WR_bars <- set_4.1_WR_bars + geom_hline(aes(yintercept=set_4.1_WR_control_int), colour="#990000", linetype="dashed")
set_4.1_WR_bars <- set_4.1_WR_bars + labs(x="", y="Root - Fresh Weight (mg)")
set_4.1_WR_bars <- set_4.1_WR_bars + geom_errorbar(aes(ymin=Average-SE, ymax=Average+SE), size=.5, width=.2)
set_4.1_WR_bars <- set_4.1_WR_bars + theme(axis.text.x = element_text(angle = 60, hjust = 1, size = 12),
                                       axis.text.y = element_text(size = 12),
                                       axis.title.x = element_blank(),
                                       axis.title.y = element_text(size = 14),
                                       legend.text = element_text(size = 16),
                                       legend.title = element_text(size = 16))
set_4.1_WR_bars <- set_4.1_WR_bars + scale_x_discrete(position = "bottom", expand = c(0,0))
set_4.1_WR_bars <- set_4.1_WR_bars + scale_y_continuous(expand = c(0,0))
set_4.1_WR_bars <- set_4.1_WR_bars + geom_text(aes(x=1, y=59, label=""), vjust=-1)
set_4.1_WR_bars

Cowplot - Set 4.1

set_4.1_wet_grid <- plot_grid(set_4.1_WS_bars + 
                                theme(plot.margin = unit(c(.1,.1,.1,.1), "cm")),
                            set_4.1_WR_bars + theme(plot.margin = unit(c(.1,.1,.1,.1), "cm")),
                            labels = c("A", "B"),
                            label_size = 24,
                            nrow = 2,
                            ncol = 1,
                            align = 'vh')
set_4.1_wet_grid

ggsave("./Plots/set_4.1_wet_grid.pdf", set_4.1_wet_grid, width = 16, height = 16)

Set 4.2

Wet Shoot

# ggplot with bars
## remove isoaltes with NA values
stat_s4.2_WS_complete <- stat_set_4.2_WS[complete.cases(stat_set_4.2_WS),]
## set the control value for Wet Shoot mg
set_4.2_WS_control_int <- as.numeric(stat_s4.2_WS_complete[23,5])
## calculate % control for each treatment
stat_s4.2_WS_complete$control <- as.numeric(stat_s4.2_WS_complete[23,5])
stat_s4.2_WS_complete <- mutate(stat_s4.2_WS_complete, p_ctrl = (100* (Average / control)))
set_4.2_WS_bars <- ggplot(stat_s4.2_WS_complete, aes(x = isolate, y = Average))
set_4.2_WS_bars <- set_4.2_WS_bars + geom_bar(stat = "identity", size=.5, fill="lightgreen")
set_4.2_WS_bars <- set_4.2_WS_bars + geom_hline(aes(yintercept=set_4.2_WS_control_int), colour="#990000", linetype="dashed")
set_4.2_WS_bars <- set_4.2_WS_bars + labs(x="", y="Shoot - Fresh Weight (mg)")
set_4.2_WS_bars <- set_4.2_WS_bars + geom_errorbar(aes(ymin=Average-SE, ymax=Average+SE), size=.5, width=.2)
set_4.2_WS_bars <- set_4.2_WS_bars + theme(axis.text.x = element_text(angle = 60, hjust = 1, size = 12),
                                       axis.text.y = element_text(size = 12),
                                       axis.title.x = element_blank(),
                                       axis.title.y = element_text(size = 14),
                                       legend.text = element_text(size = 16),
                                       legend.title = element_text(size = 16))
set_4.2_WS_bars <- set_4.2_WS_bars + scale_x_discrete(position = "bottom", expand = c(0,0))
set_4.2_WS_bars <- set_4.2_WS_bars + scale_y_continuous(expand = c(0,0))
set_4.2_WS_bars <- set_4.2_WS_bars + geom_text(aes(x=1, y=590, label="Stretch it"), vjust=-1)
set_4.2_WS_bars

Wet Root

# ggplot with bars
## remove isoaltes with NA values
stat_s4.2_WR_complete <- stat_set_4.2_WR[complete.cases(stat_set_4.2_WR),]
## set the control value for Wet Root mg
set_4.2_WR_control_int <- as.numeric(stat_s4.2_WR_complete[23,5])
## calculate % control for each treatment
stat_s4.2_WR_complete$control <- as.numeric(stat_s4.2_WR_complete[23,5])
stat_s4.2_WR_complete <- mutate(stat_s4.2_WR_complete, p_ctrl = (100* (Average / control)))
set_4.2_WR_bars <- ggplot(stat_s4.2_WR_complete, aes(x = isolate, y = Average))
set_4.2_WR_bars <- set_4.2_WR_bars + geom_bar(stat = "identity", size=.5, fill="tan")
set_4.2_WR_bars <- set_4.2_WR_bars + geom_hline(aes(yintercept=set_4.2_WR_control_int), colour="#990000", linetype="dashed")
set_4.2_WR_bars <- set_4.2_WR_bars + labs(x="", y="Root - Fresh Weight (mg)")
set_4.2_WR_bars <- set_4.2_WR_bars + geom_errorbar(aes(ymin=Average-SE, ymax=Average+SE), size=.5, width=.2)
set_4.2_WR_bars <- set_4.2_WR_bars + theme(axis.text.x = element_text(angle = 60, hjust = 1, size = 12),
                                       axis.text.y = element_text(size = 12),
                                       axis.title.x = element_blank(),
                                       axis.title.y = element_text(size = 14),
                                       legend.text = element_text(size = 16),
                                       legend.title = element_text(size = 16))
set_4.2_WR_bars <- set_4.2_WR_bars + scale_x_discrete(position = "bottom", expand = c(0,0))
set_4.2_WR_bars <- set_4.2_WR_bars + scale_y_continuous(expand = c(0,0), limits = c(0,59))
set_4.2_WR_bars <- set_4.2_WR_bars + geom_text(aes(x=isolate[6], y=55, label="317%"), hjust=0.38)
set_4.2_WR_bars <- set_4.2_WR_bars + geom_text(aes(x=isolate[8], y=51, label="305%"), hjust=0.38)
set_4.2_WR_bars

Cowplot - Set 4.2

set_4.2_wet_grid <- plot_grid(set_4.2_WS_bars + 
                                theme(plot.margin = unit(c(.1,.1,.1,.1), "cm")),
                            set_4.2_WR_bars + theme(plot.margin = unit(c(.1,.1,.1,.1), "cm")),
                            labels = c("A", "B"),
                            label_size = 24,
                            nrow = 2,
                            ncol = 1,
                            align = 'vh')
set_4.2_wet_grid

ggsave("./Plots/set_4.2_wet_grid.pdf", set_4.2_wet_grid, width = 16, height = 16)

Set 4.3

Wet Shoot

# ggplot with bars
## remove isoaltes with NA values
stat_s4.3_WS_complete <- stat_set_4.3_WS[complete.cases(stat_set_4.3_WS),]
## set the control value for Wet Shoot mg
set_4.3_WS_control_int <- as.numeric(stat_s4.3_WS_complete[25,5])
## calculate % control for each treatment
stat_s4.3_WS_complete$control <- as.numeric(stat_s4.3_WS_complete[25,5])
stat_s4.3_WS_complete <- mutate(stat_s4.3_WS_complete, p_ctrl = (100* (Average / control)))
set_4.3_WS_bars <- ggplot(stat_s4.3_WS_complete, aes(x = isolate, y = Average))
set_4.3_WS_bars <- set_4.3_WS_bars + geom_bar(stat = "identity", size=.5, fill="lightgreen")
set_4.3_WS_bars <- set_4.3_WS_bars + geom_hline(aes(yintercept=set_4.3_WS_control_int), colour="#990000", linetype="dashed")
set_4.3_WS_bars <- set_4.3_WS_bars + labs(x="", y="Shoot - Fresh Weight (mg)")
set_4.3_WS_bars <- set_4.3_WS_bars + geom_errorbar(aes(ymin=Average-SE, ymax=Average+SE), size=.5, width=.2)
set_4.3_WS_bars <- set_4.3_WS_bars + theme(axis.text.x = element_text(angle = 60, hjust = 1, size = 12),
                                       axis.text.y = element_text(size = 12),
                                       axis.title.x = element_blank(),
                                       axis.title.y = element_text(size = 14),
                                       legend.text = element_text(size = 16),
                                       legend.title = element_text(size = 16))
set_4.3_WS_bars <- set_4.3_WS_bars + scale_x_discrete(position = "bottom", expand = c(0,0))
set_4.3_WS_bars <- set_4.3_WS_bars + scale_y_continuous(expand = c(0,0))
set_4.3_WS_bars <- set_4.3_WS_bars + geom_text(aes(x=1, y=495, label="Stretch it"), vjust=-1)
set_4.3_WS_bars

Wet Root

# ggplot with bars
## remove isoaltes with NA values
stat_s4.3_WR_complete <- stat_set_4.3_WR[complete.cases(stat_set_4.3_WR),]
## set the control value for Wet Root mg
set_4.3_WR_control_int <- as.numeric(stat_s4.3_WR_complete[25,5])
## calculate % control for each treatment
stat_s4.3_WR_complete$control <- as.numeric(stat_s4.3_WR_complete[25,5])
stat_s4.3_WR_complete <- mutate(stat_s4.3_WR_complete, p_ctrl = (100* (Average / control)))
set_4.3_WR_bars <- ggplot(stat_s4.3_WR_complete, aes(x = isolate, y = Average))
set_4.3_WR_bars <- set_4.3_WR_bars + geom_bar(stat = "identity", size=.5, fill="tan")
set_4.3_WR_bars <- set_4.3_WR_bars + geom_hline(aes(yintercept=set_4.3_WR_control_int), colour="#990000", linetype="dashed")
set_4.3_WR_bars <- set_4.3_WR_bars + labs(x="", y="Root - Fresh Weight (mg)")
set_4.3_WR_bars <- set_4.3_WR_bars + geom_errorbar(aes(ymin=Average-SE, ymax=Average+SE), size=.5, width=.2)
set_4.3_WR_bars <- set_4.3_WR_bars + theme(axis.text.x = element_text(angle = 60, hjust = 1, size = 12),
                                       axis.text.y = element_text(size = 12),
                                       axis.title.x = element_blank(),
                                       axis.title.y = element_text(size = 14),
                                       legend.text = element_text(size = 16),
                                       legend.title = element_text(size = 16))
set_4.3_WR_bars <- set_4.3_WR_bars + scale_x_discrete(position = "bottom", expand = c(0,0))
set_4.3_WR_bars <- set_4.3_WR_bars + scale_y_continuous(expand = c(0,0))
set_4.3_WR_bars <- set_4.3_WR_bars + geom_text(aes(x=1, y=49, label=""), vjust=-1)
set_4.3_WR_bars

Cowplot - Set 4.3

set_4.3_wet_grid <- plot_grid(set_4.3_WS_bars + 
                                theme(plot.margin = unit(c(.1,.1,.1,.1), "cm")),
                            set_4.3_WR_bars + theme(plot.margin = unit(c(.1,.1,.1,.1), "cm")),
                            labels = c("A", "B"),
                            label_size = 24,
                            nrow = 2,
                            ncol = 1,
                            align = 'vh')
set_4.3_wet_grid

ggsave("./Plots/set_4.3_wet_grid.pdf", set_4.3_wet_grid, width = 16, height = 16)

Add Batch ID to Dry Weight Dataframes

# add batch id variable to each dataset
## Set 1
### Dry Shoot
set_1_DS_id <- set_1_DS
set_1_DS_id$batch <- c("Set 1")
### Dry Root
set_1_DR_id <- set_1_DR
set_1_DR_id$batch <- c("Set 1")
## Set 2.1
### Dry Shoot
set_2.1_DS_id <- set_2.1_DS
set_2.1_DS_id$batch <- c("Set 2.1")
### Dry Root
set_2.1_DR_id <- set_2.1_DR
set_2.1_DR_id$batch <- c("Set 2.1")
## Set 2.2
### Dry Shoot
set_2.2_DS_id <- set_2.2_DS
set_2.2_DS_id$batch <- c("Set 2.2")
### Dry Root
set_2.2_DR_id <- set_2.2_DR
set_2.2_DR_id$batch <- c("Set 2.2")
## Set 2.3
### Dry Shoot
set_2.3_DS_id <- set_2.3_DS
set_2.3_DS_id$batch <- c("Set 2.3")
### Dry Root
set_2.3_DR_id <- set_2.3_DR
set_2.3_DR_id$batch <- c("Set 2.3")
## Set 2.4
### Dry Shoot
set_2.4_DS_id <- set_2.4_DS
set_2.4_DS_id$batch <- c("Set 2.4")
### Dry Root
set_2.4_DR_id <- set_2.4_DR
set_2.4_DR_id$batch <- c("Set 2.4")
## Set 3.1
### Dry Shoot
set_3.1_DS_id <- set_3.1_DS
set_3.1_DS_id$batch <- c("Set 3.1")
### Dry Root
set_3.1_DR_id <- set_3.1_DR
set_3.1_DR_id$batch <- c("Set 3.1")
## Set 3.2
### Dry Shoot
set_3.2_DS_id <- set_3.2_DS
set_3.2_DS_id$batch <- c("Set 3.2")
### Dry Root
set_3.2_DR_id <- set_3.2_DR
set_3.2_DR_id$batch <- c("Set 3.2")
## Set 3.3
### Dry Shoot
set_3.3_DS_id <- set_3.3_DS
set_3.3_DS_id$batch <- c("Set 3.3")
### Dry Root
set_3.3_DR_id <- set_3.3_DR
set_3.3_DR_id$batch <- c("Set 3.3")
## Set 3.4
### Dry Shoot
set_3.4_DS_id <- set_3.4_DS
set_3.4_DS_id$batch <- c("Set 3.4")
### Dry Root
set_3.4_DR_id <- set_3.4_DR
set_3.4_DR_id$batch <- c("Set 3.4")
## Set 3.5
### Dry Shoot
set_3.5_DS_id <- set_3.5_DS
set_3.5_DS_id$batch <- c("Set 3.5")
### Dry Root
set_3.5_DR_id <- set_3.5_DR
set_3.5_DR_id$batch <- c("Set 3.5")
## Set 4.1
### Dry Shoot
set_4.1_DS_id <- set_4.1_DS
set_4.1_DS_id$batch <- c("Set 4.1")
### Dry Root
set_4.1_DR_id <- set_4.1_DR
set_4.1_DR_id$batch <- c("Set 4.1")
## Set 4.2
### Dry Shoot
set_4.2_DS_id <- set_4.2_DS
set_4.2_DS_id$batch <- c("Set 4.2")
### Dry Root
set_4.2_DR_id <- set_4.2_DR
set_4.2_DR_id$batch <- c("Set 4.2")
## Set 4.3
### Dry Shoot
set_4.3_DS_id <- set_4.3_DS
set_4.3_DS_id$batch <- c("Set 4.3")
### Dry Root
set_4.3_DR_id <- set_4.3_DR
set_4.3_DR_id$batch <- c("Set 4.3")

Group the Data for Plotting

#Group the datasets based on Sample ID and prep method
## Set 1
set_1_DS_grouped <- group_by(set_1_DS_id, isolate, sample, batch)
set_1_DR_grouped <- group_by(set_1_DR_id, isolate, sample, batch)
## Set 2.1
set_2.1_DS_grouped <- group_by(set_2.1_DS_id, isolate, sample, batch)
set_2.1_DR_grouped <- group_by(set_2.1_DR_id, isolate, sample, batch)
## Set 2.2
set_2.2_DS_grouped <- group_by(set_2.2_DS_id, isolate, sample, batch)
set_2.2_DR_grouped <- group_by(set_2.2_DR_id, isolate, sample, batch)
## Set 2.3
set_2.3_DS_grouped <- group_by(set_2.3_DS_id, isolate, sample, batch)
set_2.3_DR_grouped <- group_by(set_2.3_DR_id, isolate, sample, batch)
## Set 2.4
set_2.4_DS_grouped <- group_by(set_2.4_DS_id, isolate, sample, batch)
set_2.4_DR_grouped <- group_by(set_2.4_DR_id, isolate, sample, batch)
## Set 3.1
set_3.1_DS_grouped <- group_by(set_3.1_DS_id, isolate, sample, batch)
set_3.1_DR_grouped <- group_by(set_3.1_DR_id, isolate, sample, batch)
## Set 3.2
set_3.2_DS_grouped <- group_by(set_3.2_DS_id, isolate, sample, batch)
set_3.2_DR_grouped <- group_by(set_3.2_DR_id, isolate, sample, batch)
## Set 3.3
set_3.3_DS_grouped <- group_by(set_3.3_DS_id, isolate, sample, batch)
set_3.3_DR_grouped <- group_by(set_3.3_DR_id, isolate, sample, batch)
## Set 3.4
set_3.4_DS_grouped <- group_by(set_3.4_DS_id, isolate, sample, batch)
set_3.4_DR_grouped <- group_by(set_3.4_DR_id, isolate, sample, batch)
## Set 3.5
set_3.5_DS_grouped <- group_by(set_3.5_DS_id, isolate, sample, batch)
set_3.5_DR_grouped <- group_by(set_3.5_DR_id, isolate, sample, batch)
## Set 4.1
set_4.1_DS_grouped <- group_by(set_4.1_DS_id, isolate, sample, batch)
set_4.1_DR_grouped <- group_by(set_4.1_DR_id, isolate, sample, batch)
## Set 4.2
set_4.2_DS_grouped <- group_by(set_4.2_DS_id, isolate, sample, batch)
set_4.2_DR_grouped <- group_by(set_4.2_DR_id, isolate, sample, batch)
## Set 4.3
set_4.3_DS_grouped <- group_by(set_4.3_DS_id, isolate, sample, batch)
set_4.3_DR_grouped <- group_by(set_4.3_DR_id, isolate, sample, batch)

Compute stats over triplicates for plotting

# set 1
stat_set_1_DS <- summarise(set_1_DS_grouped, N=length(mg), Average=mean(mg, na.rm = TRUE), CI95=conf_int95(mg), SE=std_error(mg))
stat_set_1_DR <- summarise(set_1_DR_grouped, N=length(mg), Average=mean(mg, na.rm = TRUE), CI95=conf_int95(mg), SE=std_error(mg))
# set 2.1
stat_set_2.1_DS <- summarise(set_2.1_DS_grouped, N=length(mg), Average=mean(mg, na.rm = TRUE), CI95=conf_int95(mg), SE=std_error(mg))
stat_set_2.1_DR <- summarise(set_2.1_DR_grouped, N=length(mg), Average=mean(mg, na.rm = TRUE), CI95=conf_int95(mg), SE=std_error(mg))
# set 2.2
stat_set_2.2_DS <- summarise(set_2.2_DS_grouped, N=length(mg), Average=mean(mg, na.rm = TRUE), CI95=conf_int95(mg), SE=std_error(mg))
stat_set_2.2_DR <- summarise(set_2.2_DR_grouped, N=length(mg), Average=mean(mg, na.rm = TRUE), CI95=conf_int95(mg), SE=std_error(mg))
# set 2.3
stat_set_2.3_DS <- summarise(set_2.3_DS_grouped, N=length(mg), Average=mean(mg, na.rm = TRUE), CI95=conf_int95(mg), SE=std_error(mg))
stat_set_2.3_DR <- summarise(set_2.3_DR_grouped, N=length(mg), Average=mean(mg, na.rm = TRUE), CI95=conf_int95(mg), SE=std_error(mg))
# set 2.4
stat_set_2.4_DS <- summarise(set_2.4_DS_grouped, N=length(mg), Average=mean(mg, na.rm = TRUE), CI95=conf_int95(mg), SE=std_error(mg))
stat_set_2.4_DR <- summarise(set_2.4_DR_grouped, N=length(mg), Average=mean(mg, na.rm = TRUE), CI95=conf_int95(mg), SE=std_error(mg))
# set 3.1
stat_set_3.1_DS <- summarise(set_3.1_DS_grouped, N=length(mg), Average=mean(mg, na.rm = TRUE), CI95=conf_int95(mg), SE=std_error(mg))
stat_set_3.1_DR <- summarise(set_3.1_DR_grouped, N=length(mg), Average=mean(mg, na.rm = TRUE), CI95=conf_int95(mg), SE=std_error(mg))
# set 3.2
stat_set_3.2_DS <- summarise(set_3.2_DS_grouped, N=length(mg), Average=mean(mg, na.rm = TRUE), CI95=conf_int95(mg), SE=std_error(mg))
stat_set_3.2_DR <- summarise(set_3.2_DR_grouped, N=length(mg), Average=mean(mg, na.rm = TRUE), CI95=conf_int95(mg), SE=std_error(mg))
# set 3.3
stat_set_3.3_DS <- summarise(set_3.3_DS_grouped, N=length(mg), Average=mean(mg, na.rm = TRUE), CI95=conf_int95(mg), SE=std_error(mg))
stat_set_3.3_DR <- summarise(set_3.3_DR_grouped, N=length(mg), Average=mean(mg, na.rm = TRUE), CI95=conf_int95(mg), SE=std_error(mg))
# set 3.4
stat_set_3.4_DS <- summarise(set_3.4_DS_grouped, N=length(mg), Average=mean(mg, na.rm = TRUE), CI95=conf_int95(mg), SE=std_error(mg))
stat_set_3.4_DR <- summarise(set_3.4_DR_grouped, N=length(mg), Average=mean(mg, na.rm = TRUE), CI95=conf_int95(mg), SE=std_error(mg))
# set 3.5
stat_set_3.5_DS <- summarise(set_3.5_DS_grouped, N=length(mg), Average=mean(mg, na.rm = TRUE), CI95=conf_int95(mg), SE=std_error(mg))
stat_set_3.5_DR <- summarise(set_3.5_DR_grouped, N=length(mg), Average=mean(mg, na.rm = TRUE), CI95=conf_int95(mg), SE=std_error(mg))
# set 4.1
stat_set_4.1_DS <- summarise(set_4.1_DS_grouped, N=length(mg), Average=mean(mg, na.rm = TRUE), CI95=conf_int95(mg), SE=std_error(mg))
stat_set_4.1_DR <- summarise(set_4.1_DR_grouped, N=length(mg), Average=mean(mg, na.rm = TRUE), CI95=conf_int95(mg), SE=std_error(mg))
# set 4.2
stat_set_4.2_DS <- summarise(set_4.2_DS_grouped, N=length(mg), Average=mean(mg, na.rm = TRUE), CI95=conf_int95(mg), SE=std_error(mg))
stat_set_4.2_DR <- summarise(set_4.2_DR_grouped, N=length(mg), Average=mean(mg, na.rm = TRUE), CI95=conf_int95(mg), SE=std_error(mg))
# set 4.3
stat_set_4.3_DS <- summarise(set_4.3_DS_grouped, N=length(mg), Average=mean(mg, na.rm = TRUE), CI95=conf_int95(mg), SE=std_error(mg))
stat_set_4.3_DR <- summarise(set_4.3_DR_grouped, N=length(mg), Average=mean(mg, na.rm = TRUE), CI95=conf_int95(mg), SE=std_error(mg))

Dry Weight Plots

Set 1

Dry Shoot

# ggplot with bars
## set the control value for Dry Shoot mg
set_1_DS_control_int <- as.numeric(stat_set_1_DS[58,5])
## remove isoaltes with NA values
stat_s1_DS_complete <- stat_set_1_DS[complete.cases(stat_set_1_DS),]
## remove control-WO
stat_s1_DS_complete <- filter(stat_s1_DS_complete, isolate != "control-WO")
## calculate % control for each treatment
stat_s1_DS_complete$control <- as.numeric(stat_set_1_DS[58,5])
stat_s1_DS_complete <- mutate(stat_s1_DS_complete, p_ctrl = (100* (Average / control)))
## Make the plot
set_1_DS_bars <- ggplot(stat_s1_DS_complete, aes(x = isolate, y = Average))
set_1_DS_bars <- set_1_DS_bars + geom_bar(stat = "identity", size=.5, fill="lightgreen")
set_1_DS_bars <- set_1_DS_bars + geom_hline(aes(yintercept=set_1_DS_control_int), colour="#990000", linetype="dashed")
set_1_DS_bars <- set_1_DS_bars + labs(x="", y="Shoot - Dry Weight (mg)")
set_1_DS_bars <- set_1_DS_bars + geom_errorbar(aes(ymin=Average-SE, ymax=Average+SE), size=.5, width=.2)
#set_1_DS_bars <- set_1_DS_bars + geom_text(aes(label=sprintf("%0.0f", round(p_ctrl, digits = 0)), y=Average+SE, vjust=-0.5), hjust = 0, angle = 45)
set_1_DS_bars <- set_1_DS_bars + theme(axis.text.x = element_text(angle = 60, hjust = 1, size = 12),
                                       axis.text.y = element_text(size = 12),
                                       axis.title.x = element_blank(),
                                       axis.title.y = element_text(size = 14),
                                       legend.text = element_text(size = 16),
                                       legend.title = element_text(size = 16))
set_1_DS_bars <- set_1_DS_bars + scale_x_discrete(position = "bottom", expand = c(0,0))
set_1_DS_bars <- set_1_DS_bars + scale_y_continuous(expand = c(0,0), limits = c(0,45))
set_1_DS_bars <- set_1_DS_bars + geom_text(aes(x=isolate[11], y=42, label="205%"), hjust=0.38)
set_1_DS_bars

Dry Root

# ggplot with bars
## remove isoaltes with NA values
stat_s1_DR_complete <- stat_set_1_DR[complete.cases(stat_set_1_DR),]
## remove control-WO
stat_s1_DR_complete <- filter(stat_s1_DR_complete, isolate != "control-WO")
## set the control value for Dry Shoot mg
set_1_DR_control_int <- as.numeric(stat_s1_DR_complete[39,5])
## calculate % control for each treatment
stat_s1_DR_complete$control <- as.numeric(stat_set_1_DR[58,5])
stat_s1_DR_complete <- mutate(stat_s1_DR_complete, p_ctrl = (100* (Average / control)))
## Plot
set_1_DR_bars <- ggplot(stat_s1_DR_complete, aes(x = isolate, y = Average))
set_1_DR_bars <- set_1_DR_bars + geom_bar(stat = "identity", size=.5, fill="tan")
set_1_DR_bars <- set_1_DR_bars + geom_hline(aes(yintercept=set_1_DR_control_int), colour="#990000", linetype="dashed")
set_1_DR_bars <- set_1_DR_bars + labs(x="", y="Root - Dry Weight (mg)")
set_1_DR_bars <- set_1_DR_bars + geom_errorbar(aes(ymin=Average-SE, ymax=Average+SE), size=.5, width=.2)
set_1_DR_bars <- set_1_DR_bars + theme(axis.text.x = element_text(angle = 60, hjust = 1, size = 12),
                                       axis.text.y = element_text(size = 12),
                                       axis.title.x = element_blank(),
                                       axis.title.y = element_text(size = 14),
                                       legend.text = element_text(size = 16),
                                       legend.title = element_text(size = 16))
set_1_DR_bars <- set_1_DR_bars + scale_x_discrete(position = "bottom", expand = c(0,0))
set_1_DR_bars <- set_1_DR_bars + scale_y_continuous(expand = c(0,0), limits = c(0,19))
set_1_DR_bars <- set_1_DR_bars + geom_text(aes(x=isolate[27], y=17, label="202%"), hjust=0.38)
set_1_DR_bars

Cowplot - Set 1 - Full

set_1_dry_grid <- plot_grid(set_1_DS_bars + theme(plot.margin = unit(c(.1,.1,.1,.1), "cm")),
                            set_1_DR_bars + theme(plot.margin = unit(c(.1,.1,.1,.1), "cm")),
                            labels = c("C", "D"),
                            label_size = 24,
                            nrow = 2,
                            ncol = 1,
                            align = 'vh')
set_1_full_grid <- plot_grid(set_1_wet_grid,
                             set_1_dry_grid,
                             ncol = 2)
set_1_full_grid

ggsave("./Plots/set_1_full_grid.pdf", set_1_full_grid, width = 16, height = 16)

Set 2.1

Dry Shoot

# ggplot with bars
## set the control value for Dry Shoot mg
set_2.1_DS_control_int <- as.numeric(stat_set_2.1_DS[33,5])
## remove isoaltes with NA values
stat_s2.1_DS_complete <- stat_set_2.1_DS[complete.cases(stat_set_2.1_DS),]
## remove control-WO
stat_s2.1_DS_complete <- filter(stat_s2.1_DS_complete, isolate != "control-WO")
## calculate % control for each treatment
stat_s2.1_DS_complete$control <- as.numeric(stat_set_2.1_DS[33,5])
stat_s2.1_DS_complete <- mutate(stat_s2.1_DS_complete, p_ctrl = (100* (Average / control)))
## Make the plot
set_2.1_DS_bars <- ggplot(stat_s2.1_DS_complete, aes(x = isolate, y = Average))
set_2.1_DS_bars <- set_2.1_DS_bars + geom_bar(stat = "identity", size=.5, fill="lightgreen")
set_2.1_DS_bars <- set_2.1_DS_bars + geom_hline(aes(yintercept=set_2.1_DS_control_int), colour="#990000", linetype="dashed")
set_2.1_DS_bars <- set_2.1_DS_bars + labs(x="", y="Shoot - Dry Weight (mg)")
set_2.1_DS_bars <- set_2.1_DS_bars + geom_errorbar(aes(ymin=Average-SE, ymax=Average+SE), size=.5, width=.2)
#set_2.1_DS_bars <- set_2.1_DS_bars + geom_text(aes(label=sprintf("%0.0f", round(p_ctrl, digits = 0)), y=Average+SE, vjust=-0.5), hjust = 0, angle = 45)
set_2.1_DS_bars <- set_2.1_DS_bars + theme(axis.text.x = element_text(angle = 60, hjust = 1, size = 12),
                                       axis.text.y = element_text(size = 12),
                                       axis.title.x = element_blank(),
                                       axis.title.y = element_text(size = 14),
                                       legend.text = element_text(size = 16),
                                       legend.title = element_text(size = 16))
set_2.1_DS_bars <- set_2.1_DS_bars + scale_x_discrete(position = "bottom", expand = c(0,0))
set_2.1_DS_bars <- set_2.1_DS_bars + scale_y_continuous(expand = c(0,0), limits = c(0,45))
set_2.1_DS_bars <- set_2.1_DS_bars + geom_text(aes(x=isolate[12], y=41, label="323%"), hjust=0.38)
set_2.1_DS_bars

Dry Root

# ggplot with bars
## set the control value for Dry Root mg
## remove isoaltes with NA values
stat_s2.1_DR_complete <- stat_set_2.1_DR[complete.cases(stat_set_2.1_DR),]
## remove control-WO
stat_s2.1_DR_complete <- filter(stat_s2.1_DR_complete, isolate != "control-WO")
set_2.1_DR_control_int <- as.numeric(stat_s2.1_DR_complete[31,5])
## calculate % control for each treatment
stat_s2.1_DR_complete$control <- as.numeric(stat_set_2.1_DR[31,5])
stat_s2.1_DR_complete <- mutate(stat_s2.1_DR_complete, p_ctrl = (100* (Average / control)))
## Plot
set_2.1_DR_bars <- ggplot(stat_s2.1_DR_complete, aes(x = isolate, y = Average))
set_2.1_DR_bars <- set_2.1_DR_bars + geom_bar(stat = "identity", size=.5, fill="tan")
set_2.1_DR_bars <- set_2.1_DR_bars + geom_hline(aes(yintercept=set_2.1_DR_control_int), colour="#990000", linetype="dashed")
set_2.1_DR_bars <- set_2.1_DR_bars + labs(x="", y="Root - Dry Weight (mg)")
set_2.1_DR_bars <- set_2.1_DR_bars + geom_errorbar(aes(ymin=Average-SE, ymax=Average+SE), size=.5, width=.2)
set_2.1_DR_bars <- set_2.1_DR_bars + theme(axis.text.x = element_text(angle = 60, hjust = 1, size = 12),
                                       axis.text.y = element_text(size = 12),
                                       axis.title.x = element_blank(),
                                       axis.title.y = element_text(size = 14),
                                       legend.text = element_text(size = 16),
                                       legend.title = element_text(size = 16))
set_2.1_DR_bars <- set_2.1_DR_bars + scale_x_discrete(position = "bottom", expand = c(0,0))
set_2.1_DR_bars <- set_2.1_DR_bars + scale_y_continuous(expand = c(0,0), limits = c(0,11.5))
set_2.1_DR_bars <- set_2.1_DR_bars + geom_text(aes(x=isolate[24], y=10.5, label="190%"), hjust=0.38)
set_2.1_DR_bars <- set_2.1_DR_bars + geom_text(aes(x=isolate[21], y=10, label="182%"), hjust=0.38)
set_2.1_DR_bars

Cowplot - Set 2.1 - Full

set_2.1_dry_grid <- plot_grid(set_2.1_DS_bars + theme(plot.margin = unit(c(.1,.1,.1,.1), "cm")),
                            set_2.1_DR_bars + theme(plot.margin = unit(c(.1,.1,.1,.1), "cm")),
                            labels = c("C", "D"),
                            label_size = 24,
                            nrow = 2,
                            ncol = 1,
                            align = 'vh')
set_2.1_full_grid <- plot_grid(set_2.1_wet_grid,
                             set_2.1_dry_grid,
                             ncol = 2)
set_2.1_full_grid

ggsave("./Plots/set_2.1_full_grid.pdf", set_2.1_full_grid, width = 16, height = 16)

Set 2.2

Dry Shoot

# ggplot with bars
## set the control value for Dry Shoot mg
set_2.2_DS_control_int <- as.numeric(stat_set_2.2_DS[33,5])
## remove isoaltes with NA values
stat_s2.2_DS_complete <- stat_set_2.2_DS[complete.cases(stat_set_2.2_DS),]
## remove control-WO
stat_s2.2_DS_complete <- filter(stat_s2.2_DS_complete, isolate != "control-WO")
## calculate % control for each treatment
stat_s2.2_DS_complete$control <- as.numeric(stat_set_2.2_DS[33,5])
stat_s2.2_DS_complete <- mutate(stat_s2.2_DS_complete, p_ctrl = (100* (Average / control)))
## Make the plot
set_2.2_DS_bars <- ggplot(stat_s2.2_DS_complete, aes(x = isolate, y = Average))
set_2.2_DS_bars <- set_2.2_DS_bars + geom_bar(stat = "identity", size=.5, fill="lightgreen")
set_2.2_DS_bars <- set_2.2_DS_bars + geom_hline(aes(yintercept=set_2.2_DS_control_int), colour="#990000", linetype="dashed")
set_2.2_DS_bars <- set_2.2_DS_bars + labs(x="", y="Shoot - Dry Weight (mg)")
set_2.2_DS_bars <- set_2.2_DS_bars + geom_errorbar(aes(ymin=Average-SE, ymax=Average+SE), size=.5, width=.2)
#set_2.2_DS_bars <- set_2.2_DS_bars + geom_text(aes(label=sprintf("%0.0f", round(p_ctrl, digits = 0)), y=Average+SE, vjust=-0.5), hjust = 0, angle = 45)
set_2.2_DS_bars <- set_2.2_DS_bars + theme(axis.text.x = element_text(angle = 60, hjust = 1, size = 12),
                                       axis.text.y = element_text(size = 12),
                                       axis.title.x = element_blank(),
                                       axis.title.y = element_text(size = 14),
                                       legend.text = element_text(size = 16),
                                       legend.title = element_text(size = 16))
set_2.2_DS_bars <- set_2.2_DS_bars + scale_x_discrete(position = "bottom", expand = c(0,0))
set_2.2_DS_bars <- set_2.2_DS_bars + scale_y_continuous(expand = c(0,0), limits = c(0,65))
set_2.2_DS_bars <- set_2.2_DS_bars + geom_text(aes(x=isolate[26], y=61, label="318%"), hjust=0.38)
set_2.2_DS_bars

Dry Root

# ggplot with bars
## set the control value for Dry Root mg
## remove isoaltes with NA values
stat_s2.2_DR_complete <- stat_set_2.2_DR[complete.cases(stat_set_2.2_DR),]
## remove control-WO
stat_s2.2_DR_complete <- filter(stat_s2.2_DR_complete, isolate != "control-WO")
set_2.2_DR_control_int <- as.numeric(stat_s2.2_DR_complete[32,5])
## calculate % control for each treatment
stat_s2.2_DR_complete$control <- as.numeric(stat_set_2.2_DR[32,5])
stat_s2.2_DR_complete <- mutate(stat_s2.2_DR_complete, p_ctrl = (100* (Average / control)))
## Plot
set_2.2_DR_bars <- ggplot(stat_s2.2_DR_complete, aes(x = isolate, y = Average))
set_2.2_DR_bars <- set_2.2_DR_bars + geom_bar(stat = "identity", size=.5, fill="tan")
set_2.2_DR_bars <- set_2.2_DR_bars + geom_hline(aes(yintercept=set_2.2_DR_control_int), colour="#990000", linetype="dashed")
set_2.2_DR_bars <- set_2.2_DR_bars + labs(x="", y="Root - Dry Weight (mg)")
set_2.2_DR_bars <- set_2.2_DR_bars + geom_errorbar(aes(ymin=Average-SE, ymax=Average+SE), size=.5, width=.2)
set_2.2_DR_bars <- set_2.2_DR_bars + theme(axis.text.x = element_text(angle = 60, hjust = 1, size = 12),
                                       axis.text.y = element_text(size = 12),
                                       axis.title.x = element_blank(),
                                       axis.title.y = element_text(size = 14),
                                       legend.text = element_text(size = 16),
                                       legend.title = element_text(size = 16))
set_2.2_DR_bars <- set_2.2_DR_bars + scale_x_discrete(position = "bottom", expand = c(0,0))
set_2.2_DR_bars <- set_2.2_DR_bars + scale_y_continuous(expand = c(0,0), limits = c(0,13.8))
set_2.2_DR_bars <- set_2.2_DR_bars + geom_text(aes(x=isolate[26], y=13, label="237%"), hjust=0.38)
set_2.2_DR_bars

Cowplot - Set 2.2 - Full

set_2.2_dry_grid <- plot_grid(set_2.2_DS_bars + theme(plot.margin = unit(c(.1,.1,.1,.1), "cm")),
                            set_2.2_DR_bars + theme(plot.margin = unit(c(.1,.1,.1,.1), "cm")),
                            labels = c("C", "D"),
                            label_size = 24,
                            nrow = 2,
                            ncol = 1,
                            align = 'vh')
set_2.2_full_grid <- plot_grid(set_2.2_wet_grid,
                             set_2.2_dry_grid,
                             ncol = 2)
set_2.2_full_grid

ggsave("./Plots/set_2.2_full_grid.pdf", set_2.2_full_grid, width = 16, height = 16)

Set 2.3

Dry Shoot

# ggplot with bars
## set the control value for Dry Shoot mg
set_2.3_DS_control_int <- as.numeric(stat_set_2.3_DS[28,5])
## remove isoaltes with NA values
stat_s2.3_DS_complete <- stat_set_2.3_DS[complete.cases(stat_set_2.3_DS),]
## remove control-WO
stat_s2.3_DS_complete <- filter(stat_s2.3_DS_complete, isolate != "control-WO")
## calculate % control for each treatment
stat_s2.3_DS_complete$control <- as.numeric(stat_set_2.3_DS[28,5])
stat_s2.3_DS_complete <- mutate(stat_s2.3_DS_complete, p_ctrl = (100* (Average / control)))
## Make the plot
set_2.3_DS_bars <- ggplot(stat_s2.3_DS_complete, aes(x = isolate, y = Average))
set_2.3_DS_bars <- set_2.3_DS_bars + geom_bar(stat = "identity", size=.5, fill="lightgreen")
set_2.3_DS_bars <- set_2.3_DS_bars + geom_hline(aes(yintercept=set_2.3_DS_control_int), colour="#990000", linetype="dashed")
set_2.3_DS_bars <- set_2.3_DS_bars + labs(x="", y="Shoot - Dry Weight (mg)")
set_2.3_DS_bars <- set_2.3_DS_bars + geom_errorbar(aes(ymin=Average-SE, ymax=Average+SE), size=.5, width=.2)
#set_2.3_DS_bars <- set_2.3_DS_bars + geom_text(aes(label=sprintf("%0.0f", round(p_ctrl, digits = 0)), y=Average+SE, vjust=-0.5), hjust = 0, angle = 45)
set_2.3_DS_bars <- set_2.3_DS_bars + theme(axis.text.x = element_text(angle = 60, hjust = 1, size = 12),
                                       axis.text.y = element_text(size = 12),
                                       axis.title.x = element_blank(),
                                       axis.title.y = element_text(size = 14),
                                       legend.text = element_text(size = 16),
                                       legend.title = element_text(size = 16))
set_2.3_DS_bars <- set_2.3_DS_bars + scale_x_discrete(position = "bottom", expand = c(0,0))
set_2.3_DS_bars <- set_2.3_DS_bars + scale_y_continuous(expand = c(0,0), limits = c(0,45))
#set_2.3_DS_bars <- set_2.3_DS_bars + geom_text(aes(x=isolate[26], y=61, label="318%"), hjust=0.38)
set_2.3_DS_bars

Dry Root

# ggplot with bars
## set the control value for Dry Root mg
## remove isoaltes with NA values
stat_s2.3_DR_complete <- stat_set_2.3_DR[complete.cases(stat_set_2.3_DR),]
## remove control-WO
stat_s2.3_DR_complete <- filter(stat_s2.3_DR_complete, isolate != "control-WO")
set_2.3_DR_control_int <- as.numeric(stat_s2.3_DR_complete[25,5])
## calculate % control for each treatment
stat_s2.3_DR_complete$control <- as.numeric(stat_set_2.3_DR[25,5])
stat_s2.3_DR_complete <- mutate(stat_s2.3_DR_complete, p_ctrl = (100* (Average / control)))
## Plot
set_2.3_DR_bars <- ggplot(stat_s2.3_DR_complete, aes(x = isolate, y = Average))
set_2.3_DR_bars <- set_2.3_DR_bars + geom_bar(stat = "identity", size=.5, fill="tan")
set_2.3_DR_bars <- set_2.3_DR_bars + geom_hline(aes(yintercept=set_2.3_DR_control_int), colour="#990000", linetype="dashed")
set_2.3_DR_bars <- set_2.3_DR_bars + labs(x="", y="Root - Dry Weight (mg)")
set_2.3_DR_bars <- set_2.3_DR_bars + geom_errorbar(aes(ymin=Average-SE, ymax=Average+SE), size=.5, width=.2)
set_2.3_DR_bars <- set_2.3_DR_bars + theme(axis.text.x = element_text(angle = 60, hjust = 1, size = 12),
                                       axis.text.y = element_text(size = 12),
                                       axis.title.x = element_blank(),
                                       axis.title.y = element_text(size = 14),
                                       legend.text = element_text(size = 16),
                                       legend.title = element_text(size = 16))
set_2.3_DR_bars <- set_2.3_DR_bars + scale_x_discrete(position = "bottom", expand = c(0,0))
set_2.3_DR_bars <- set_2.3_DR_bars + scale_y_continuous(expand = c(0,0), limits = c(0,17.5))
#set_2.3_DR_bars <- set_2.3_DR_bars + geom_text(aes(x=isolate[26], y=13, label="237%"), hjust=0.38)
set_2.3_DR_bars

Cowplot - Set 2.3 - Full

set_2.3_dry_grid <- plot_grid(set_2.3_DS_bars + theme(plot.margin = unit(c(.1,.1,.1,.1), "cm")),
                            set_2.3_DR_bars + theme(plot.margin = unit(c(.1,.1,.1,.1), "cm")),
                            labels = c("C", "D"),
                            label_size = 24,
                            nrow = 2,
                            ncol = 1,
                            align = 'vh')
set_2.3_full_grid <- plot_grid(set_2.3_wet_grid,
                             set_2.3_dry_grid,
                             ncol = 2)
set_2.3_full_grid

ggsave("./Plots/set_2.3_full_grid.pdf", set_2.3_full_grid, width = 16, height = 16)

Set 2.4

Dry Shoot

# ggplot with bars
## set the control value for Dry Shoot mg
set_2.4_DS_control_int <- as.numeric(stat_set_2.4_DS[37,5])
## remove isoaltes with NA values
stat_s2.4_DS_complete <- stat_set_2.4_DS[complete.cases(stat_set_2.4_DS),]
## remove control-WO
stat_s2.4_DS_complete <- filter(stat_s2.4_DS_complete, isolate != "control-WO")
## calculate % control for each treatment
stat_s2.4_DS_complete$control <- as.numeric(stat_set_2.4_DS[37,5])
stat_s2.4_DS_complete <- mutate(stat_s2.4_DS_complete, p_ctrl = (100* (Average / control)))
## Make the plot
set_2.4_DS_bars <- ggplot(stat_s2.4_DS_complete, aes(x = isolate, y = Average))
set_2.4_DS_bars <- set_2.4_DS_bars + geom_bar(stat = "identity", size=.5, fill="lightgreen")
set_2.4_DS_bars <- set_2.4_DS_bars + geom_hline(aes(yintercept=set_2.4_DS_control_int), colour="#990000", linetype="dashed")
set_2.4_DS_bars <- set_2.4_DS_bars + labs(x="", y="Shoot - Dry Weight (mg)")
set_2.4_DS_bars <- set_2.4_DS_bars + geom_errorbar(aes(ymin=Average-SE, ymax=Average+SE), size=.5, width=.2)
#set_2.4_DS_bars <- set_2.4_DS_bars + geom_text(aes(label=sprintf("%0.0f", round(p_ctrl, digits = 0)), y=Average+SE, vjust=-0.5), hjust = 0, angle = 45)
set_2.4_DS_bars <- set_2.4_DS_bars + theme(axis.text.x = element_text(angle = 60, hjust = 1, size = 12),
                                       axis.text.y = element_text(size = 12),
                                       axis.title.x = element_blank(),
                                       axis.title.y = element_text(size = 14),
                                       legend.text = element_text(size = 16),
                                       legend.title = element_text(size = 16))
set_2.4_DS_bars <- set_2.4_DS_bars + scale_x_discrete(position = "bottom", expand = c(0,0))
set_2.4_DS_bars <- set_2.4_DS_bars + scale_y_continuous(expand = c(0,0), limits = c(0,55))
set_2.4_DS_bars <- set_2.4_DS_bars + geom_text(aes(x=isolate[25], y=51, label="251%"), hjust=0.38)
set_2.4_DS_bars <- set_2.4_DS_bars + geom_text(aes(x=isolate[34], y=47, label="262%"), hjust=0.38)
set_2.4_DS_bars

Dry Root

# ggplot with bars
## set the control value for Dry Root mg
## remove isoaltes with NA values
stat_s2.4_DR_complete <- stat_set_2.4_DR[complete.cases(stat_set_2.4_DR),]
## remove control-WO
stat_s2.4_DR_complete <- filter(stat_s2.4_DR_complete, isolate != "control-WO")
set_2.4_DR_control_int <- as.numeric(stat_s2.4_DR_complete[36,5])
## calculate % control for each treatment
stat_s2.4_DR_complete$control <- as.numeric(stat_set_2.4_DR[36,5])
stat_s2.4_DR_complete <- mutate(stat_s2.4_DR_complete, p_ctrl = (100* (Average / control)))
## Plot
set_2.4_DR_bars <- ggplot(stat_s2.4_DR_complete, aes(x = isolate, y = Average))
set_2.4_DR_bars <- set_2.4_DR_bars + geom_bar(stat = "identity", size=.5, fill="tan")
set_2.4_DR_bars <- set_2.4_DR_bars + geom_hline(aes(yintercept=set_2.4_DR_control_int), colour="#990000", linetype="dashed")
set_2.4_DR_bars <- set_2.4_DR_bars + labs(x="", y="Root - Dry Weight (mg)")
set_2.4_DR_bars <- set_2.4_DR_bars + geom_errorbar(aes(ymin=Average-SE, ymax=Average+SE), size=.5, width=.2)
set_2.4_DR_bars <- set_2.4_DR_bars + theme(axis.text.x = element_text(angle = 60, hjust = 1, size = 12),
                                       axis.text.y = element_text(size = 12),
                                       axis.title.x = element_blank(),
                                       axis.title.y = element_text(size = 14),
                                       legend.text = element_text(size = 16),
                                       legend.title = element_text(size = 16))
set_2.4_DR_bars <- set_2.4_DR_bars + scale_x_discrete(position = "bottom", expand = c(0,0))
set_2.4_DR_bars <- set_2.4_DR_bars + scale_y_continuous(expand = c(0,0), limits = c(0,14))
set_2.4_DR_bars <- set_2.4_DR_bars + geom_text(aes(x=isolate[34], y=10, label="198%"), hjust=0.38)
set_2.4_DR_bars

Cowplot - Set 2.4 - Full

set_2.4_dry_grid <- plot_grid(set_2.4_DS_bars + theme(plot.margin = unit(c(.1,.1,.1,.1), "cm")),
                            set_2.4_DR_bars + theme(plot.margin = unit(c(.1,.1,.1,.1), "cm")),
                            labels = c("C", "D"),
                            label_size = 24,
                            nrow = 2,
                            ncol = 1,
                            align = 'vh')
set_2.4_full_grid <- plot_grid(set_2.4_wet_grid,
                             set_2.4_dry_grid,
                             ncol = 2)
set_2.4_full_grid

ggsave("./Plots/set_2.4_full_grid.pdf", set_2.4_full_grid, width = 16, height = 16)

Set 3.1

Dry Shoot

# ggplot with bars
## remove isoaltes with NA values
stat_s3.1_DS_complete <- stat_set_3.1_DS[complete.cases(stat_set_3.1_DS),]
## set the control value for Dry Shoot mg
set_3.1_DS_control_int <- as.numeric(stat_s3.1_DS_complete[36,5])
## calculate % control for each treatment
stat_s3.1_DS_complete$control <- as.numeric(stat_s3.1_DS_complete[36,5])
stat_s3.1_DS_complete <- mutate(stat_s3.1_DS_complete, p_ctrl = (100* (Average / control)))
set_3.1_DS_bars <- ggplot(stat_s3.1_DS_complete, aes(x = isolate, y = Average))
set_3.1_DS_bars <- set_3.1_DS_bars + geom_bar(stat = "identity", size=.5, fill="lightgreen")
set_3.1_DS_bars <- set_3.1_DS_bars + geom_hline(aes(yintercept=set_3.1_DS_control_int), colour="#990000", linetype="dashed")
set_3.1_DS_bars <- set_3.1_DS_bars + labs(x="", y="Shoot - Dry Weight (mg)")
set_3.1_DS_bars <- set_3.1_DS_bars + geom_errorbar(aes(ymin=Average-SE, ymax=Average+SE), size=.5, width=.2)
set_3.1_DS_bars <- set_3.1_DS_bars + theme(axis.text.x = element_text(angle = 60, hjust = 1, size = 12),
                                       axis.text.y = element_text(size = 12),
                                       axis.title.x = element_blank(),
                                       axis.title.y = element_text(size = 14),
                                       legend.text = element_text(size = 16),
                                       legend.title = element_text(size = 16))
set_3.1_DS_bars <- set_3.1_DS_bars + scale_x_discrete(position = "bottom", expand = c(0,0))
set_3.1_DS_bars <- set_3.1_DS_bars + scale_y_continuous(expand = c(0,0), limits = c(0,45))
#set_3.1_DS_bars <- set_3.1_DS_bars + geom_text(aes(x=isolate[18], y=814, label="233%"), hjust=0.38)
set_3.1_DS_bars <- set_3.1_DS_bars + geom_text(aes(x=isolate[33], y=36, label="277%"), hjust=0.38)
set_3.1_DS_bars

Dry Root

# ggplot with bars
## remove isoaltes with NA values
stat_s3.1_DR_complete <- stat_set_3.1_DR[complete.cases(stat_set_3.1_DR),]
## set the control value for Dry Shoot mg
set_3.1_DR_control_int <- as.numeric(stat_s3.1_DR_complete[36,5])
## calculate % control for each treatment
stat_s3.1_DR_complete$control <- as.numeric(stat_s3.1_DR_complete[36,5])
stat_s3.1_DR_complete <- mutate(stat_s3.1_DR_complete, p_ctrl = (100* (Average / control)))
set_3.1_DR_bars <- ggplot(stat_s3.1_DR_complete, aes(x = isolate, y = Average))
set_3.1_DR_bars <- set_3.1_DR_bars + geom_bar(stat = "identity", size=.5, fill="tan")
set_3.1_DR_bars <- set_3.1_DR_bars + geom_hline(aes(yintercept=set_3.1_DR_control_int), colour="#990000", linetype="dashed")
set_3.1_DR_bars <- set_3.1_DR_bars + labs(x="", y="Root - Dry Weight (mg)")
set_3.1_DR_bars <- set_3.1_DR_bars + geom_errorbar(aes(ymin=Average-SE, ymax=Average+SE), size=.5, width=.2)
set_3.1_DR_bars <- set_3.1_DR_bars + theme(axis.text.x = element_text(angle = 60, hjust = 1, size = 12),
                                       axis.text.y = element_text(size = 12),
                                       axis.title.x = element_blank(),
                                       axis.title.y = element_text(size = 14),
                                       legend.text = element_text(size = 16),
                                       legend.title = element_text(size = 16))
set_3.1_DR_bars <- set_3.1_DR_bars + scale_x_discrete(position = "bottom", expand = c(0,0))
set_3.1_DR_bars <- set_3.1_DR_bars + scale_y_continuous(expand = c(0,0), limits = c(0,7.9))
set_3.1_DR_bars <- set_3.1_DR_bars + geom_text(aes(x=isolate[18], y=6, label="211%"), hjust=0.38)
set_3.1_DR_bars <- set_3.1_DR_bars + geom_text(aes(x=isolate[23], y=7.7, label="250%"), hjust=0.38)
set_3.1_DR_bars

Cowplot - Set 3.1 - Full

set_3.1_dry_grid <- plot_grid(set_3.1_DS_bars + theme(plot.margin = unit(c(.1,.1,.1,.1), "cm")),
                            set_3.1_DR_bars + theme(plot.margin = unit(c(.1,.1,.1,.1), "cm")),
                            labels = c("C", "D"),
                            label_size = 24,
                            nrow = 2,
                            ncol = 1,
                            align = 'vh')
set_3.1_full_grid <- plot_grid(set_3.1_wet_grid,
                             set_3.1_dry_grid,
                             ncol = 2)
set_3.1_full_grid

ggsave("./Plots/set_3.1_full_grid.pdf", set_3.1_full_grid, width = 16, height = 16)

Set 3.2

Dry Shoot

# ggplot with bars
## remove isoaltes with NA values
stat_s3.2_DS_complete <- stat_set_3.2_DS[complete.cases(stat_set_3.2_DS),]
## set the control value for Dry Shoot mg
set_3.2_DS_control_int <- as.numeric(stat_s3.2_DS_complete[24,5])
## calculate % control for each treatment
stat_s3.2_DS_complete$control <- as.numeric(stat_s3.2_DS_complete[24,5])
stat_s3.2_DS_complete <- mutate(stat_s3.2_DS_complete, p_ctrl = (100* (Average / control)))
set_3.2_DS_bars <- ggplot(stat_s3.2_DS_complete, aes(x = isolate, y = Average))
set_3.2_DS_bars <- set_3.2_DS_bars + geom_bar(stat = "identity", size=.5, fill="lightgreen")
set_3.2_DS_bars <- set_3.2_DS_bars + geom_hline(aes(yintercept=set_3.2_DS_control_int), colour="#990000", linetype="dashed")
set_3.2_DS_bars <- set_3.2_DS_bars + labs(x="", y="Shoot - Dry Weight (mg)")
set_3.2_DS_bars <- set_3.2_DS_bars + geom_errorbar(aes(ymin=Average-SE, ymax=Average+SE), size=.5, width=.2)
set_3.2_DS_bars <- set_3.2_DS_bars + theme(axis.text.x = element_text(angle = 60, hjust = 1, size = 12),
                                       axis.text.y = element_text(size = 12),
                                       axis.title.x = element_blank(),
                                       axis.title.y = element_text(size = 14),
                                       legend.text = element_text(size = 16),
                                       legend.title = element_text(size = 16))
set_3.2_DS_bars <- set_3.2_DS_bars + scale_x_discrete(position = "bottom", expand = c(0,0))
set_3.2_DS_bars <- set_3.2_DS_bars + scale_y_continuous(expand = c(0,0), limits = c(0,29))
set_3.2_DS_bars

Dry Root

# ggplot with bars
## remove isoaltes with NA values
stat_s3.2_DR_complete <- stat_set_3.2_DR[complete.cases(stat_set_3.2_DR),]
## set the control value for Dry Shoot mg
set_3.2_DR_control_int <- as.numeric(stat_s3.2_DR_complete[24,5])
## calculate % control for each treatment
stat_s3.2_DR_complete$control <- as.numeric(stat_s3.2_DR_complete[24,5])
stat_s3.2_DR_complete <- mutate(stat_s3.2_DR_complete, p_ctrl = (100* (Average / control)))
set_3.2_DR_bars <- ggplot(stat_s3.2_DR_complete, aes(x = isolate, y = Average))
set_3.2_DR_bars <- set_3.2_DR_bars + geom_bar(stat = "identity", size=.5, fill="tan")
set_3.2_DR_bars <- set_3.2_DR_bars + geom_hline(aes(yintercept=set_3.2_DR_control_int), colour="#990000", linetype="dashed")
set_3.2_DR_bars <- set_3.2_DR_bars + labs(x="", y="Root - Dry Weight (mg)")
set_3.2_DR_bars <- set_3.2_DR_bars + geom_errorbar(aes(ymin=Average-SE, ymax=Average+SE), size=.5, width=.2)
set_3.2_DR_bars <- set_3.2_DR_bars + theme(axis.text.x = element_text(angle = 60, hjust = 1, size = 12),
                                       axis.text.y = element_text(size = 12),
                                       axis.title.x = element_blank(),
                                       axis.title.y = element_text(size = 14),
                                       legend.text = element_text(size = 16),
                                       legend.title = element_text(size = 16))
set_3.2_DR_bars <- set_3.2_DR_bars + scale_x_discrete(position = "bottom", expand = c(0,0))
set_3.2_DR_bars <- set_3.2_DR_bars + scale_y_continuous(expand = c(0,0), limits = c(0,7.9))
#set_3.2_DR_bars <- set_3.2_DR_bars + geom_text(aes(x=isolate[18], y=6, label="211%"), hjust=0.38)
#set_3.2_DR_bars <- set_3.2_DR_bars + geom_text(aes(x=isolate[23], y=7.7, label="250%"), hjust=0.38)
set_3.2_DR_bars

Cowplot - Set 3.2 - Full

set_3.2_dry_grid <- plot_grid(set_3.2_DS_bars + theme(plot.margin = unit(c(.1,.1,.1,.1), "cm")),
                            set_3.2_DR_bars + theme(plot.margin = unit(c(.1,.1,.1,.1), "cm")),
                            labels = c("C", "D"),
                            label_size = 24,
                            nrow = 2,
                            ncol = 1,
                            align = 'vh')
set_3.2_full_grid <- plot_grid(set_3.2_wet_grid,
                             set_3.2_dry_grid,
                             ncol = 2)
set_3.2_full_grid

ggsave("./Plots/set_3.2_full_grid.pdf", set_3.2_full_grid, width = 16, height = 16)

Set 3.3

Dry Shoot

# ggplot with bars
## remove isoaltes with NA values
stat_s3.3_DS_complete <- stat_set_3.3_DS[complete.cases(stat_set_3.3_DS),]
## set the control value for Dry Shoot mg
set_3.3_DS_control_int <- as.numeric(stat_s3.3_DS_complete[37,5])
## calculate % control for each treatment
stat_s3.3_DS_complete$control <- as.numeric(stat_s3.3_DS_complete[37,5])
stat_s3.3_DS_complete <- mutate(stat_s3.3_DS_complete, p_ctrl = (100* (Average / control)))
set_3.3_DS_bars <- ggplot(stat_s3.3_DS_complete, aes(x = isolate, y = Average))
set_3.3_DS_bars <- set_3.3_DS_bars + geom_bar(stat = "identity", size=.5, fill="lightgreen")
set_3.3_DS_bars <- set_3.3_DS_bars + geom_hline(aes(yintercept=set_3.3_DS_control_int), colour="#990000", linetype="dashed")
set_3.3_DS_bars <- set_3.3_DS_bars + labs(x="", y="Shoot - Dry Weight (mg)")
set_3.3_DS_bars <- set_3.3_DS_bars + geom_errorbar(aes(ymin=Average-SE, ymax=Average+SE), size=.5, width=.2)
set_3.3_DS_bars <- set_3.3_DS_bars + theme(axis.text.x = element_text(angle = 60, hjust = 1, size = 12),
                                       axis.text.y = element_text(size = 12),
                                       axis.title.x = element_blank(),
                                       axis.title.y = element_text(size = 14),
                                       legend.text = element_text(size = 16),
                                       legend.title = element_text(size = 16))
set_3.3_DS_bars <- set_3.3_DS_bars + scale_x_discrete(position = "bottom", expand = c(0,0))
set_3.3_DS_bars <- set_3.3_DS_bars + scale_y_continuous(expand = c(0,0), limits = c(0,49))
set_3.3_DS_bars

Dry Root

# ggplot with bars
## remove isoaltes with NA values
stat_s3.3_DR_complete <- stat_set_3.3_DR[complete.cases(stat_set_3.3_DR),]
## set the control value for Dry Shoot mg
set_3.3_DR_control_int <- as.numeric(stat_s3.3_DR_complete[37,5])
## calculate % control for each treatment
stat_s3.3_DR_complete$control <- as.numeric(stat_s3.3_DR_complete[37,5])
stat_s3.3_DR_complete <- mutate(stat_s3.3_DR_complete, p_ctrl = (100* (Average / control)))
set_3.3_DR_bars <- ggplot(stat_s3.3_DR_complete, aes(x = isolate, y = Average))
set_3.3_DR_bars <- set_3.3_DR_bars + geom_bar(stat = "identity", size=.5, fill="tan")
set_3.3_DR_bars <- set_3.3_DR_bars + geom_hline(aes(yintercept=set_3.3_DR_control_int), colour="#990000", linetype="dashed")
set_3.3_DR_bars <- set_3.3_DR_bars + labs(x="", y="Root - Dry Weight (mg)")
set_3.3_DR_bars <- set_3.3_DR_bars + geom_errorbar(aes(ymin=Average-SE, ymax=Average+SE), size=.5, width=.2)
set_3.3_DR_bars <- set_3.3_DR_bars + theme(axis.text.x = element_text(angle = 60, hjust = 1, size = 12),
                                       axis.text.y = element_text(size = 12),
                                       axis.title.x = element_blank(),
                                       axis.title.y = element_text(size = 14),
                                       legend.text = element_text(size = 16),
                                       legend.title = element_text(size = 16))
set_3.3_DR_bars <- set_3.3_DR_bars + scale_x_discrete(position = "bottom", expand = c(0,0))
set_3.3_DR_bars <- set_3.3_DR_bars + scale_y_continuous(expand = c(0,0), limits = c(0,8.9))
set_3.3_DR_bars

Cowplot - Set 3.3 - Full

set_3.3_dry_grid <- plot_grid(set_3.3_DS_bars + theme(plot.margin = unit(c(.1,.1,.1,.1), "cm")),
                            set_3.3_DR_bars + theme(plot.margin = unit(c(.1,.1,.1,.1), "cm")),
                            labels = c("C", "D"),
                            label_size = 24,
                            nrow = 2,
                            ncol = 1,
                            align = 'vh')
set_3.3_full_grid <- plot_grid(set_3.3_wet_grid,
                             set_3.3_dry_grid,
                             ncol = 2)
set_3.3_full_grid

ggsave("./Plots/set_3.3_full_grid.pdf", set_3.3_full_grid, width = 16, height = 16)

Set 3.4

Dry Shoot

# ggplot with bars
## remove isoaltes with NA values
stat_s3.4_DS_complete <- stat_set_3.4_DS[complete.cases(stat_set_3.4_DS),]
## set the control value for Dry Shoot mg
set_3.4_DS_control_int <- as.numeric(stat_s3.4_DS_complete[36,5])
## calculate % control for each treatment
stat_s3.4_DS_complete$control <- as.numeric(stat_s3.4_DS_complete[36,5])
stat_s3.4_DS_complete <- mutate(stat_s3.4_DS_complete, p_ctrl = (100* (Average / control)))
set_3.4_DS_bars <- ggplot(stat_s3.4_DS_complete, aes(x = isolate, y = Average))
set_3.4_DS_bars <- set_3.4_DS_bars + geom_bar(stat = "identity", size=.5, fill="lightgreen")
set_3.4_DS_bars <- set_3.4_DS_bars + geom_hline(aes(yintercept=set_3.4_DS_control_int), colour="#990000", linetype="dashed")
set_3.4_DS_bars <- set_3.4_DS_bars + labs(x="", y="Shoot - Dry Weight (mg)")
set_3.4_DS_bars <- set_3.4_DS_bars + geom_errorbar(aes(ymin=Average-SE, ymax=Average+SE), size=.5, width=.2)
set_3.4_DS_bars <- set_3.4_DS_bars + theme(axis.text.x = element_text(angle = 60, hjust = 1, size = 12),
                                       axis.text.y = element_text(size = 12),
                                       axis.title.x = element_blank(),
                                       axis.title.y = element_text(size = 14),
                                       legend.text = element_text(size = 16),
                                       legend.title = element_text(size = 16))
set_3.4_DS_bars <- set_3.4_DS_bars + scale_x_discrete(position = "bottom", expand = c(0,0))
set_3.4_DS_bars <- set_3.4_DS_bars + scale_y_continuous(expand = c(0,0), limits = c(0,35))
set_3.4_DS_bars <- set_3.4_DS_bars + geom_text(aes(x=isolate[17], y=31.5, label="150%"), hjust=0.38)
set_3.4_DS_bars

Dry Root

# ggplot with bars
## remove isoaltes with NA values
stat_s3.4_DR_complete <- stat_set_3.4_DR[complete.cases(stat_set_3.4_DR),]
## set the control value for Dry Shoot mg
set_3.4_DR_control_int <- as.numeric(stat_s3.4_DR_complete[36,5])
## calculate % control for each treatment
stat_s3.4_DR_complete$control <- as.numeric(stat_s3.4_DR_complete[36,5])
stat_s3.4_DR_complete <- mutate(stat_s3.4_DR_complete, p_ctrl = (100* (Average / control)))
set_3.4_DR_bars <- ggplot(stat_s3.4_DR_complete, aes(x = isolate, y = Average))
set_3.4_DR_bars <- set_3.4_DR_bars + geom_bar(stat = "identity", size=.5, fill="tan")
set_3.4_DR_bars <- set_3.4_DR_bars + geom_hline(aes(yintercept=set_3.4_DR_control_int), colour="#990000", linetype="dashed")
set_3.4_DR_bars <- set_3.4_DR_bars + labs(x="", y="Root - Dry Weight (mg)")
set_3.4_DR_bars <- set_3.4_DR_bars + geom_errorbar(aes(ymin=Average-SE, ymax=Average+SE), size=.5, width=.2)
set_3.4_DR_bars <- set_3.4_DR_bars + theme(axis.text.x = element_text(angle = 60, hjust = 1, size = 12),
                                       axis.text.y = element_text(size = 12),
                                       axis.title.x = element_blank(),
                                       axis.title.y = element_text(size = 14),
                                       legend.text = element_text(size = 16),
                                       legend.title = element_text(size = 16))
set_3.4_DR_bars <- set_3.4_DR_bars + scale_x_discrete(position = "bottom", expand = c(0,0))
set_3.4_DR_bars <- set_3.4_DR_bars + scale_y_continuous(expand = c(0,0), limits = c(0,8.9))
set_3.4_DR_bars <- set_3.4_DR_bars + geom_text(aes(x=isolate[6], y=6.3, label="134%"), hjust=0.38)
set_3.4_DR_bars

Cowplot - Set 3.4 - Full

set_3.4_dry_grid <- plot_grid(set_3.4_DS_bars + theme(plot.margin = unit(c(.1,.1,.1,.1), "cm")),
                            set_3.4_DR_bars + theme(plot.margin = unit(c(.1,.1,.1,.1), "cm")),
                            labels = c("C", "D"),
                            label_size = 24,
                            nrow = 2,
                            ncol = 1,
                            align = 'vh')
set_3.4_full_grid <- plot_grid(set_3.4_wet_grid,
                             set_3.4_dry_grid,
                             ncol = 2)
set_3.4_full_grid

ggsave("./Plots/set_3.4_full_grid.pdf", set_3.4_full_grid, width = 16, height = 16)

Set 3.5

Dry Shoot

# ggplot with bars
## remove isoaltes with NA values
stat_s3.5_DS_complete <- stat_set_3.5_DS[complete.cases(stat_set_3.5_DS),]
## set the control value for Dry Shoot mg
set_3.5_DS_control_int <- as.numeric(stat_s3.5_DS_complete[20,5])
## calculate % control for each treatment
stat_s3.5_DS_complete$control <- as.numeric(stat_s3.5_DS_complete[20,5])
stat_s3.5_DS_complete <- mutate(stat_s3.5_DS_complete, p_ctrl = (100* (Average / control)))
set_3.5_DS_bars <- ggplot(stat_s3.5_DS_complete, aes(x = isolate, y = Average))
set_3.5_DS_bars <- set_3.5_DS_bars + geom_bar(stat = "identity", size=.5, fill="lightgreen")
set_3.5_DS_bars <- set_3.5_DS_bars + geom_hline(aes(yintercept=set_3.5_DS_control_int), colour="#990000", linetype="dashed")
set_3.5_DS_bars <- set_3.5_DS_bars + labs(x="", y="Shoot - Dry Weight (mg)")
set_3.5_DS_bars <- set_3.5_DS_bars + geom_errorbar(aes(ymin=Average-SE, ymax=Average+SE), size=.5, width=.2)
set_3.5_DS_bars <- set_3.5_DS_bars + theme(axis.text.x = element_text(angle = 60, hjust = 1, size = 12),
                                       axis.text.y = element_text(size = 12),
                                       axis.title.x = element_blank(),
                                       axis.title.y = element_text(size = 14),
                                       legend.text = element_text(size = 16),
                                       legend.title = element_text(size = 16))
set_3.5_DS_bars <- set_3.5_DS_bars + scale_x_discrete(position = "bottom", expand = c(0,0))
set_3.5_DS_bars <- set_3.5_DS_bars + scale_y_continuous(expand = c(0,0), limits = c(0,29))
set_3.5_DS_bars <- set_3.5_DS_bars + geom_text(aes(x=isolate[11], y=27, label="150%"), hjust=0.38)
set_3.5_DS_bars

Dry Root

# ggplot with bars
## remove isoaltes with NA values
stat_s3.5_DR_complete <- stat_set_3.5_DR[complete.cases(stat_set_3.5_DR),]
## set the control value for Dry Shoot mg
set_3.5_DR_control_int <- as.numeric(stat_s3.5_DR_complete[20,5])
## calculate % control for each treatment
stat_s3.5_DR_complete$control <- as.numeric(stat_s3.5_DR_complete[20,5])
stat_s3.5_DR_complete <- mutate(stat_s3.5_DR_complete, p_ctrl = (100* (Average / control)))
set_3.5_DR_bars <- ggplot(stat_s3.5_DR_complete, aes(x = isolate, y = Average))
set_3.5_DR_bars <- set_3.5_DR_bars + geom_bar(stat = "identity", size=.5, fill="tan")
set_3.5_DR_bars <- set_3.5_DR_bars + geom_hline(aes(yintercept=set_3.5_DR_control_int), colour="#990000", linetype="dashed")
set_3.5_DR_bars <- set_3.5_DR_bars + labs(x="", y="Root - Dry Weight (mg)")
set_3.5_DR_bars <- set_3.5_DR_bars + geom_errorbar(aes(ymin=Average-SE, ymax=Average+SE), size=.5, width=.2)
set_3.5_DR_bars <- set_3.5_DR_bars + theme(axis.text.x = element_text(angle = 60, hjust = 1, size = 12),
                                       axis.text.y = element_text(size = 12),
                                       axis.title.x = element_blank(),
                                       axis.title.y = element_text(size = 14),
                                       legend.text = element_text(size = 16),
                                       legend.title = element_text(size = 16))
set_3.5_DR_bars <- set_3.5_DR_bars + scale_x_discrete(position = "bottom", expand = c(0,0))
set_3.5_DR_bars <- set_3.5_DR_bars + scale_y_continuous(expand = c(0,0), limits = c(0,5.7))
set_3.5_DR_bars

Cowplot - Set 3.5 - Full

set_3.5_dry_grid <- plot_grid(set_3.5_DS_bars + theme(plot.margin = unit(c(.1,.1,.1,.1), "cm")),
                            set_3.5_DR_bars + theme(plot.margin = unit(c(.1,.1,.1,.1), "cm")),
                            labels = c("C", "D"),
                            label_size = 24,
                            nrow = 2,
                            ncol = 1,
                            align = 'vh')
set_3.5_full_grid <- plot_grid(set_3.5_wet_grid,
                             set_3.5_dry_grid,
                             ncol = 2)
set_3.5_full_grid

ggsave("./Plots/set_3.5_full_grid.pdf", set_3.5_full_grid, width = 16, height = 16)

Set 4.1

Dry Shoot

# ggplot with bars
## remove isoaltes with NA values
stat_s4.1_DS_complete <- stat_set_4.1_DS[complete.cases(stat_set_4.1_DS),]
## set the control value for Dry Shoot mg
set_4.1_DS_control_int <- as.numeric(stat_s4.1_DS_complete[37,5])
## calculate % control for each treatment
stat_s4.1_DS_complete$control <- as.numeric(stat_s4.1_DS_complete[37,5])
stat_s4.1_DS_complete <- mutate(stat_s4.1_DS_complete, p_ctrl = (100* (Average / control)))
set_4.1_DS_bars <- ggplot(stat_s4.1_DS_complete, aes(x = isolate, y = Average))
set_4.1_DS_bars <- set_4.1_DS_bars + geom_bar(stat = "identity", size=.5, fill="lightgreen")
set_4.1_DS_bars <- set_4.1_DS_bars + geom_hline(aes(yintercept=set_4.1_DS_control_int), colour="#990000", linetype="dashed")
set_4.1_DS_bars <- set_4.1_DS_bars + labs(x="", y="Shoot - Dry Weight (mg)")
set_4.1_DS_bars <- set_4.1_DS_bars + geom_errorbar(aes(ymin=Average-SE, ymax=Average+SE), size=.5, width=.2)
set_4.1_DS_bars <- set_4.1_DS_bars + theme(axis.text.x = element_text(angle = 60, hjust = 1, size = 12),
                                       axis.text.y = element_text(size = 12),
                                       axis.title.x = element_blank(),
                                       axis.title.y = element_text(size = 14),
                                       legend.text = element_text(size = 16),
                                       legend.title = element_text(size = 16))
set_4.1_DS_bars <- set_4.1_DS_bars + scale_x_discrete(position = "bottom", expand = c(0,0))
set_4.1_DS_bars <- set_4.1_DS_bars + scale_y_continuous(expand = c(0,0), limits = c(0,45))
set_4.1_DS_bars <- set_4.1_DS_bars + geom_text(aes(x=isolate[16], y=37, label="165%"), hjust=0.38)
set_4.1_DS_bars <- set_4.1_DS_bars + geom_text(aes(x=isolate[25], y=42, label="180%"), hjust=0.38)
set_4.1_DS_bars

Dry Root

# ggplot with bars
## remove isoaltes with NA values
stat_s4.1_DR_complete <- stat_set_4.1_DR[complete.cases(stat_set_4.1_DR),]
## set the control value for Dry Shoot mg
set_4.1_DR_control_int <- as.numeric(stat_s4.1_DR_complete[37,5])
## calculate % control for each treatment
stat_s4.1_DR_complete$control <- as.numeric(stat_s4.1_DR_complete[37,5])
stat_s4.1_DR_complete <- mutate(stat_s4.1_DR_complete, p_ctrl = (100* (Average / control)))
set_4.1_DR_bars <- ggplot(stat_s4.1_DR_complete, aes(x = isolate, y = Average))
set_4.1_DR_bars <- set_4.1_DR_bars + geom_bar(stat = "identity", size=.5, fill="tan")
set_4.1_DR_bars <- set_4.1_DR_bars + geom_hline(aes(yintercept=set_4.1_DR_control_int), colour="#990000", linetype="dashed")
set_4.1_DR_bars <- set_4.1_DR_bars + labs(x="", y="Root - Dry Weight (mg)")
set_4.1_DR_bars <- set_4.1_DR_bars + geom_errorbar(aes(ymin=Average-SE, ymax=Average+SE), size=.5, width=.2)
set_4.1_DR_bars <- set_4.1_DR_bars + theme(axis.text.x = element_text(angle = 60, hjust = 1, size = 12),
                                       axis.text.y = element_text(size = 12),
                                       axis.title.x = element_blank(),
                                       axis.title.y = element_text(size = 14),
                                       legend.text = element_text(size = 16),
                                       legend.title = element_text(size = 16))
set_4.1_DR_bars <- set_4.1_DR_bars + scale_x_discrete(position = "bottom", expand = c(0,0))
set_4.1_DR_bars <- set_4.1_DR_bars + scale_y_continuous(expand = c(0,0), limits = c(0,5.7))
set_4.1_DR_bars

Cowplot - Set 4.1 - Full

set_4.1_dry_grid <- plot_grid(set_4.1_DS_bars + theme(plot.margin = unit(c(.1,.1,.1,.1), "cm")),
                            set_4.1_DR_bars + theme(plot.margin = unit(c(.1,.1,.1,.1), "cm")),
                            labels = c("C", "D"),
                            label_size = 24,
                            nrow = 2,
                            ncol = 1,
                            align = 'vh')
set_4.1_full_grid <- plot_grid(set_4.1_wet_grid,
                             set_4.1_dry_grid,
                             ncol = 2)
set_4.1_full_grid

ggsave("./Plots/set_4.1_full_grid.pdf", set_4.1_full_grid, width = 16, height = 16)

Set 4.2

Dry Shoot

# ggplot with bars
## remove isoaltes with NA values
stat_s4.2_DS_complete <- stat_set_4.2_DS[complete.cases(stat_set_4.2_DS),]
## set the control value for Dry Shoot mg
set_4.2_DS_control_int <- as.numeric(stat_s4.2_DS_complete[23,5])
## calculate % control for each treatment
stat_s4.2_DS_complete$control <- as.numeric(stat_s4.2_DS_complete[23,5])
stat_s4.2_DS_complete <- mutate(stat_s4.2_DS_complete, p_ctrl = (100* (Average / control)))
set_4.2_DS_bars <- ggplot(stat_s4.2_DS_complete, aes(x = isolate, y = Average))
set_4.2_DS_bars <- set_4.2_DS_bars + geom_bar(stat = "identity", size=.5, fill="lightgreen")
set_4.2_DS_bars <- set_4.2_DS_bars + geom_hline(aes(yintercept=set_4.2_DS_control_int), colour="#990000", linetype="dashed")
set_4.2_DS_bars <- set_4.2_DS_bars + labs(x="", y="Shoot - Dry Weight (mg)")
set_4.2_DS_bars <- set_4.2_DS_bars + geom_errorbar(aes(ymin=Average-SE, ymax=Average+SE), size=.5, width=.2)
set_4.2_DS_bars <- set_4.2_DS_bars + theme(axis.text.x = element_text(angle = 60, hjust = 1, size = 12),
                                       axis.text.y = element_text(size = 12),
                                       axis.title.x = element_blank(),
                                       axis.title.y = element_text(size = 14),
                                       legend.text = element_text(size = 16),
                                       legend.title = element_text(size = 16))
set_4.2_DS_bars <- set_4.2_DS_bars + scale_x_discrete(position = "bottom", expand = c(0,0))
set_4.2_DS_bars <- set_4.2_DS_bars + scale_y_continuous(expand = c(0,0), limits = c(0,52))
set_4.2_DS_bars <- set_4.2_DS_bars + geom_text(aes(x=isolate[8], y=42, label="242%"), hjust=0.38)
set_4.2_DS_bars <- set_4.2_DS_bars + geom_text(aes(x=isolate[17], y=38, label="203%"), hjust=0.38)
set_4.2_DS_bars

Dry Root

# ggplot with bars
## remove isoaltes with NA values
stat_s4.2_DR_complete <- stat_set_4.2_DR[complete.cases(stat_set_4.2_DR),]
## set the control value for Dry Shoot mg
set_4.2_DR_control_int <- as.numeric(stat_s4.2_DR_complete[23,5])
## calculate % control for each treatment
stat_s4.2_DR_complete$control <- as.numeric(stat_s4.2_DR_complete[23,5])
stat_s4.2_DR_complete <- mutate(stat_s4.2_DR_complete, p_ctrl = (100* (Average / control)))
set_4.2_DR_bars <- ggplot(stat_s4.2_DR_complete, aes(x = isolate, y = Average))
set_4.2_DR_bars <- set_4.2_DR_bars + geom_bar(stat = "identity", size=.5, fill="tan")
set_4.2_DR_bars <- set_4.2_DR_bars + geom_hline(aes(yintercept=set_4.2_DR_control_int), colour="#990000", linetype="dashed")
set_4.2_DR_bars <- set_4.2_DR_bars + labs(x="", y="Root - Dry Weight (mg)")
set_4.2_DR_bars <- set_4.2_DR_bars + geom_errorbar(aes(ymin=Average-SE, ymax=Average+SE), size=.5, width=.2)
set_4.2_DR_bars <- set_4.2_DR_bars + theme(axis.text.x = element_text(angle = 60, hjust = 1, size = 12),
                                       axis.text.y = element_text(size = 12),
                                       axis.title.x = element_blank(),
                                       axis.title.y = element_text(size = 14),
                                       legend.text = element_text(size = 16),
                                       legend.title = element_text(size = 16))
set_4.2_DR_bars <- set_4.2_DR_bars + scale_x_discrete(position = "bottom", expand = c(0,0))
set_4.2_DR_bars <- set_4.2_DR_bars + scale_y_continuous(expand = c(0,0), limits = c(0,5.7))
set_4.2_DR_bars <- set_4.2_DR_bars + geom_text(aes(x=isolate[6], y=4.5, label="392%"), hjust=0.38)
set_4.2_DR_bars <- set_4.2_DR_bars + geom_text(aes(x=isolate[8], y=4.7, label="420%"), hjust=0.38)
set_4.2_DR_bars

Cowplot - Set 4.2 - Full

set_4.2_dry_grid <- plot_grid(set_4.2_DS_bars + theme(plot.margin = unit(c(.1,.1,.1,.1), "cm")),
                            set_4.2_DR_bars + theme(plot.margin = unit(c(.1,.1,.1,.1), "cm")),
                            labels = c("C", "D"),
                            label_size = 24,
                            nrow = 2,
                            ncol = 1,
                            align = 'vh')
set_4.2_full_grid <- plot_grid(set_4.2_wet_grid,
                             set_4.2_dry_grid,
                             ncol = 2)
set_4.2_full_grid

ggsave("./Plots/set_4.2_full_grid.pdf", set_4.2_full_grid, width = 16, height = 16)

Set 4.3

Dry Shoot

# ggplot with bars
## remove isoaltes with NA values
stat_s4.3_DS_complete <- stat_set_4.3_DS[complete.cases(stat_set_4.3_DS),]
## set the control value for Dry Shoot mg
set_4.3_DS_control_int <- as.numeric(stat_s4.3_DS_complete[25,5])
## calculate % control for each treatment
stat_s4.3_DS_complete$control <- as.numeric(stat_s4.3_DS_complete[25,5])
stat_s4.3_DS_complete <- mutate(stat_s4.3_DS_complete, p_ctrl = (100* (Average / control)))
set_4.3_DS_bars <- ggplot(stat_s4.3_DS_complete, aes(x = isolate, y = Average))
set_4.3_DS_bars <- set_4.3_DS_bars + geom_bar(stat = "identity", size=.5, fill="lightgreen")
set_4.3_DS_bars <- set_4.3_DS_bars + geom_hline(aes(yintercept=set_4.3_DS_control_int), colour="#990000", linetype="dashed")
set_4.3_DS_bars <- set_4.3_DS_bars + labs(x="", y="Shoot - Dry Weight (mg)")
set_4.3_DS_bars <- set_4.3_DS_bars + geom_errorbar(aes(ymin=Average-SE, ymax=Average+SE), size=.5, width=.2)
set_4.3_DS_bars <- set_4.3_DS_bars + theme(axis.text.x = element_text(angle = 60, hjust = 1, size = 12),
                                       axis.text.y = element_text(size = 12),
                                       axis.title.x = element_blank(),
                                       axis.title.y = element_text(size = 14),
                                       legend.text = element_text(size = 16),
                                       legend.title = element_text(size = 16))
set_4.3_DS_bars <- set_4.3_DS_bars + scale_x_discrete(position = "bottom", expand = c(0,0))
set_4.3_DS_bars <- set_4.3_DS_bars + scale_y_continuous(expand = c(0,0), limits = c(0,35))
set_4.3_DS_bars

Dry Root

# ggplot with bars
## remove isoaltes with NA values
stat_s4.3_DR_complete <- stat_set_4.3_DR[complete.cases(stat_set_4.3_DR),]
## set the control value for Dry Shoot mg
set_4.3_DR_control_int <- as.numeric(stat_s4.3_DR_complete[25,5])
## calculate % control for each treatment
stat_s4.3_DR_complete$control <- as.numeric(stat_s4.3_DR_complete[25,5])
stat_s4.3_DR_complete <- mutate(stat_s4.3_DR_complete, p_ctrl = (100* (Average / control)))
set_4.3_DR_bars <- ggplot(stat_s4.3_DR_complete, aes(x = isolate, y = Average))
set_4.3_DR_bars <- set_4.3_DR_bars + geom_bar(stat = "identity", size=.5, fill="tan")
set_4.3_DR_bars <- set_4.3_DR_bars + geom_hline(aes(yintercept=set_4.3_DR_control_int), colour="#990000", linetype="dashed")
set_4.3_DR_bars <- set_4.3_DR_bars + labs(x="", y="Root - Dry Weight (mg)")
set_4.3_DR_bars <- set_4.3_DR_bars + geom_errorbar(aes(ymin=Average-SE, ymax=Average+SE), size=.5, width=.2)
set_4.3_DR_bars <- set_4.3_DR_bars + theme(axis.text.x = element_text(angle = 60, hjust = 1, size = 12),
                                       axis.text.y = element_text(size = 12),
                                       axis.title.x = element_blank(),
                                       axis.title.y = element_text(size = 14),
                                       legend.text = element_text(size = 16),
                                       legend.title = element_text(size = 16))
set_4.3_DR_bars <- set_4.3_DR_bars + scale_x_discrete(position = "bottom", expand = c(0,0))
set_4.3_DR_bars <- set_4.3_DR_bars + scale_y_continuous(expand = c(0,0), limits = c(0,3.9))
set_4.3_DR_bars

Cowplot - Set 4.3 - Full

set_4.3_dry_grid <- plot_grid(set_4.3_DS_bars + theme(plot.margin = unit(c(.1,.1,.1,.1), "cm")),
                            set_4.3_DR_bars + theme(plot.margin = unit(c(.1,.1,.1,.1), "cm")),
                            labels = c("C", "D"),
                            label_size = 24,
                            nrow = 2,
                            ncol = 1,
                            align = 'vh')
set_4.3_full_grid <- plot_grid(set_4.3_wet_grid,
                             set_4.3_dry_grid,
                             ncol = 2)
set_4.3_full_grid

ggsave("./Plots/set_4.3_full_grid.pdf", set_4.3_full_grid, width = 16, height = 16)

Table 2

Statistically Significant Isolates based on Wet Weight Measruements

Create Master Dataframe of Plot Weights

# Create lists of dfs for wet shoot complete cases
wet_shoot_stat_list <- mget(ls(pattern = "stat_.+_WS_complete"))
wet_root_stat_list <- mget(ls(pattern = "stat_.+_WR_complete"))
dry_shoot_stat_list <- mget(ls(pattern = "stat_.+_DS_complete"))
dry_root_stat_list <- mget(ls(pattern = "stat_.+_DR_complete"))
## Bind rows
wet_shoot_master <- bind_rows(wet_shoot_stat_list)
wet_root_master <- bind_rows(wet_root_stat_list)
dry_shoot_master <- bind_rows(dry_shoot_stat_list)
dry_root_master <- bind_rows(dry_root_stat_list)

create master dataframe of lsmeans_data for each sample type

trt.vs.control

p-value correction for multiple testing using DunnettX method

confidence level used = 0.95 or alpha = 0.05

Read in csv files

# Make lists of files for dataframes
## Dry Root files
paths.lsm.dun.DR <- list.files(path = "./lsmeans_summary_tables/", pattern = "*.DR.csv", recursive = T, full.names = T)
## Dry Shoot files
paths.lsm.dun.DS <- list.files(path = "./lsmeans_summary_tables/", pattern = "*.DS.csv", recursive = T, full.names = T)
## Wet Root files
paths.lsm.dun.WR <- list.files(path = "./lsmeans_summary_tables/", pattern = "*.WR.csv", recursive = T, full.names = T)
## Wet Shoot files
paths.lsm.dun.WS <- list.files(path = "./lsmeans_summary_tables/", pattern = "*.WS.csv", recursive = T, full.names = T)
# Read in lists of DR files
list.lsm.dun.DR <- lapply(paths.lsm.dun.DR, read_csv)
# Read in lists of DS files
list.lsm.dun.DS <- lapply(paths.lsm.dun.DS, read_csv)
# Read in lists of WR files
list.lsm.dun.WR <- lapply(paths.lsm.dun.WR, read_csv)
# Read in lists of WS files
list.lsm.dun.WS <- lapply(paths.lsm.dun.WS, read_csv)

Bind Rows

Make a master dataframe

# Dry Roots
lsm.dun.DR.master <- bind_rows(list.lsm.dun.DR)
# Dry Shoots
lsm.dun.DS.master <- bind_rows(list.lsm.dun.DS)
# Wet Roots
lsm.dun.WR.master <- bind_rows(list.lsm.dun.WR)
# Wet Shoots
lsm.dun.WS.master <- bind_rows(list.lsm.dun.WS)

Add Isolate names and response type

# Dry Roots
## Extract Isolate ID from contrast variable
lsm.dun.DR.master <- lsm.dun.DR.master %>% 
  extract(contrast, into = "Isolate", regex = "(^[0-9]+)", remove = FALSE)
## Create BCW-ID variable
lsm.dun.DR.master <- lsm.dun.DR.master %>% 
  mutate("BCW-ID" = paste0("BCW-", Isolate)) %>%
  mutate("Response" = "Dry Root")
# Dry Shoots
## Extract Isolate ID from contrast variable
lsm.dun.DS.master <- lsm.dun.DS.master %>% 
  extract(contrast, into = "Isolate", regex = "(^[0-9]+)", remove = FALSE)
## Create BCW-ID variable
lsm.dun.DS.master <- lsm.dun.DS.master %>%
  mutate("BCW-ID" = paste0("BCW-", Isolate)) %>%
  mutate("Response" = "Dry Shoot")
# Wet Roots
## Extract Isolate ID from contrast variable
lsm.dun.WR.master <- lsm.dun.WR.master %>% 
  extract(contrast, into = "Isolate", regex = "(^[0-9]+)", remove = FALSE)
## Create BCW-ID variable
lsm.dun.WR.master <- lsm.dun.WR.master %>%
  mutate("BCW-ID" = paste0("BCW-", Isolate)) %>%
  mutate("Response" = "Fresh Root")
# Wet Shoots
## Extract Isolate ID from contrast variable
lsm.dun.WS.master <- lsm.dun.WS.master %>% 
  extract(contrast, into = "Isolate", regex = "(^[0-9]+)", remove = FALSE)
## Create BCW-ID variable
lsm.dun.WS.master <- lsm.dun.WS.master %>%
  mutate("BCW-ID" = paste0("BCW-", Isolate)) %>%
  mutate("Response" = "Fresh Shoot")

Add Percent Control Variable

# Dry Root
lsm.dun.DR.master$p_control <- dry_root_master$p_ctrl[match(lsm.dun.DR.master$Isolate,
                                                            dry_root_master$isolate)]
# Dry Shoot
lsm.dun.DS.master$p_control <- dry_shoot_master$p_ctrl[match(lsm.dun.DS.master$Isolate,
                                                            dry_shoot_master$isolate)]
# Wet Root
lsm.dun.WR.master$p_control <- wet_root_master$p_ctrl[match(lsm.dun.WR.master$Isolate,
                                                            wet_root_master$isolate)]
# Wet Shoot
lsm.dun.WS.master$p_control <- wet_shoot_master$p_ctrl[match(lsm.dun.WS.master$Isolate,
                                                            wet_shoot_master$isolate)]

Select variables and filter

# Wet Shoot
t2.WS.master <- lsm.dun.WS.master %>%
  select(`BCW-ID`, estimate, SE, p.value, Response, p_control) %>%
  filter(p_control > 100 &
           p.value < 0.1 &
           estimate > 0)
# Wet Root
t2.WR.master <- lsm.dun.WR.master %>%
  select(`BCW-ID`, estimate, SE, p.value, Response, p_control) %>%
  filter(p_control > 100 &
           p.value < 0.1 &
           estimate > 0)
# Dry Shoot
t2.DS.master <- lsm.dun.DS.master %>%
  select(`BCW-ID`, estimate, SE, p.value, Response, p_control) %>%
  filter(p_control > 100 &
           p.value < 0.1 &
           estimate > 0)
# Dry Root
t2.DR.master <- lsm.dun.DR.master %>%
  select(`BCW-ID`, estimate, SE, p.value, Response, p_control) %>%
  filter(p_control > 100 &
           p.value < 0.1 &
           estimate > 0)
# Combine
t2_list_master <- mget(ls(pattern = "t2.*.master"))
t2.master <- bind_rows(t2_list_master)

Add Genus info

# read in abb to bcw map file
abb_bcw_labels <- read_csv("./metadata/abb_genome_bcw_labels.csv", col_names = TRUE)

Parsed with column specification:
cols(
  BCW_ID = col_character(),
  ABB_ID = col_character()
)

abb_bcw_labels$BCW_ID <- sub("_", "-", abb_bcw_labels$BCW_ID)
# read in sourmash lca data of whole genome signatures
sourmash_lca <- read_csv("./metadata/lca-classify-all-k31-gtdb89.csv", col_names = TRUE)

Parsed with column specification:
cols(
  ID = col_character(),
  status = col_character(),
  superkingdom = col_character(),
  phylum = col_character(),
  class = col_character(),
  order = col_character(),
  family = col_character(),
  genus = col_character(),
  species = col_character(),
  strain = col_logical()
)

## empty cells are 'unassigned'
sourmash_lca <- sourmash_lca %>%
  replace(., is.na(.), "Unassigned")

Error: Assigned data `values` must be compatible with existing data.
ℹ Error occurred for column `strain`.
x Can't convert <character> to <logical>.
Run `rlang::last_error()` to see where the error occurred.

rr t2.master.2 <- t2.master # Add Genus variable t2.master.2 <- t2.master.2 %>% full_join(sourmash_lca, by = c(-ID = )) %>% drop_na()